Jon Todd Hoeksema

Professor of Physics (Research)

Stanford University

United States

Research Interests

Explore related searches

Professors in United States Professors in Astronomy Astronomy professors in United States

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Jon Todd Hoeksema is a Professor of Physics (Research) at Stanford University in the United States. His research encompasses solar physics, particularly focusing on magnetic field calibration, data assimilation techniques, and the dynamics of solar active regions. Recent articles highlight his contributions to understanding solar flows, vector magnetograms, and the interplay between kinetic and magnetic helicity.

Articles (16)

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2021

Collaborators (6)

Ruizhu Chen

Stanford University

UNITED STATES

View details

Gherardo Valori

Max Planck Institute for Solar System Research

GERMANY

View details

THOMAS WOODS

University of Colorado Boulder

UNITED STATES

View details

Junwei Zhao

Stanford University

UNITED STATES

View details

Lisa Upton

UNITED STATES

View details

G. C. Ho

Johns Hopkins University

UNITED STATES

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Jon Todd Hoeksema

Research Interests

Explore related searches

Contact this professor

About

Articles (16)

Toward a Consensus for Multi-Sourced Photospheric Line-of-Sight Magnetic Field Cross-Calibration

The Sun’s Large-Scale Flows I: Measurements of Differential Rotation & Torsional Oscillation

The Relationship between Kinetic and Magnetic Helicity in Solar Active Regions

Ensemble Kalman Filter Data Assimilation into the Surface Flux Transport Model to Infer Surface Flows: An Observing System Simulation Experiment

The Dependence of Joy’s Law and Mean Tilt as a Function of Flux Emergence Phase

SuperSynthIA: Physics-ready Full-disk Vector Magnetograms from HMI, Hinode, and Machine Learning

Vol. 55, Issue 3 (Heliophysics 2024 Decadal Whitepapers)

Vol. 55, Issue 3 (Heliophysics 2024 Decadal Whitepapers)

Vol. 55, Issue 3 (Heliophysics 2024 Decadal Whitepapers)

Vol. 55, Issue 3 (Heliophysics 2024 Decadal Whitepapers)

Vol. 55, Issue 3 (Heliophysics 2024 Decadal Whitepapers)

Vol. 55, Issue 3 (Heliophysics 2024 Decadal Whitepapers)

Large-scale Spatial Cross-calibration of Hinode/SOT-SP and SDO/HMI

Inferring Maps of the Sun’s Far-side Unsigned Magnetic Flux from Far-side Helioseismic Images Using Machine Learning Techniques

SynthIA: A Synthetic Inversion Approximation for the Stokes Vector Fusing SDO and Hinode into a Virtual Observatory

Improvement of the Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Inversion Code

Collaborators (6)

Ruizhu Chen

Gherardo Valori

THOMAS WOODS

Junwei Zhao

Lisa Upton

G. C. Ho

Make your next move.