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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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7 results for “AGN”

Identifying AGN host galaxies with convolutional neural networksastro-ph.GA

CNN identifies AGN host galaxies from Sloan Digital Sky Survey data.

problem Identifying AGN host galaxies using traditional methods is time-consuming.

method Trained a convolutional neural network on 210,000 galaxies.

result CNN can distinguish AGN host galaxies from non-active galaxies.

AGN CNN galaxy classification spectroscopy

2022-12-15abs ↗pdf ↗

PICZL: Image-based Photometric Redshifts for AGNastro-ph.GA

PICZL improves photometric redshifts for AGN in all-sky surveys.

problem Challenges in accurately computing photo-z for AGN due to interplay of SMBH and host galaxy emissions.

method PICZL uses an ensemble of CNNs with cross-channel integration of image and catalog data, leveraging Gaussian mixture models.

result PICZL achieves a photo-z variance of 4.5% and outlier fraction of 5.6% on a validation sample of 8098 AGN, outperforming previous methods.

AGN photometric redshifts machine learning CNNs cross-channel integration

2024-11-11abs ↗pdf ↗

Nesterov acceleration despite very noisy gradientsstat.ML

AGNES accelerates gradient descent with noisy gradients.

problem Minimizing smooth convex and strongly convex functions with noisy gradients.

method Generalization of Nesterov's accelerated gradient descent algorithm for noisy conditions.

result AGNES achieves acceleration for noisy gradients with a constant of proportionality up to 1.

Nesterov acceleration gradient descent noisy gradients overparametrized machine learning signal-to-noise ratio

2023-02-10abs ↗pdf ↗

Finding active galactic nuclei through Finkastro-ph.IM

Fink AGN classifier achieves high accuracy in classifying active galactic nuclei.

problem Classifying active galactic nuclei from astronomical data.

method Built features from photometric points and color estimation. Used active learning for optimized training sample. Applied traditional machine learning algorithms.

result Achieved 98.0% accuracy in classifying real alerts from ZTF.

AGN classification Fink broker astronomical data active learning symbolic regression

2022-11-20abs ↗pdf ↗

A probabilistic approach to emission-line galaxy classificationastro-ph.GA

We invoke a Gaussian mixture model (GMM) to jointly analyse two traditional emission-line classification schemes of galaxy ionization sources: the Baldwin-Phillips-Terlevich (BPT) and $\rm W_{Hα}$ vs. [NII]/H $α$ (WHAN) diagrams, using spectroscopic data from the Sloan Digital Sky Survey Data Release 7 and SEAGal/STARLI…

2017-03-22abs ↗pdf ↗

Identifying Transients in the Dark Energy Survey using Convolutional Neural Networksastro-ph.IM

CNNs improve transient detection in DES-SN images.

problem Automated identification of transients in astronomical images.

method Convolutional Neural Networks (CNNs) for image classification.

result CNNs achieve efficiency in identifying non-artifacts from artifacts.

Astronomy Dark Energy Survey CNNs Image Classification Transient Detection

2022-03-18abs ↗pdf ↗

Single parameter galaxy classification: The Principal Curve through the multi-dimensional space of galaxy propertiesastro-ph.CO

We propose to describe the variety of galaxies from SDSS by using only one affine parameter. To this aim, we build the Principal Curve (P-curve) passing through the spine of the data point cloud, considering the eigenspace derived from Principal Component Analysis of morphological, physical and photometric galaxy prope…

2012-07-01abs ↗pdf ↗