Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

Posted by dbos Chicago

Kavli Affiliate: Brian Nord | First 5 Authors: Sreevani Jarugula, Brian Nord, Abhijith Gandrakota, Aleksandra Ćiprijanović, | Summary: In this work, we present a scalable approach for inferring the dark energy equation-of-state parameter ($w$) from a population of strong gravitational lens images using Simulation-Based Inference (SBI). Strong gravitational lensing offers crucial insights into cosmology, but […]


Continue.. Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Posted by dbos Stanford

Kavli Affiliate: Sven Herrmann | First 5 Authors: Artem Poliszczuk, Dan Wilkins, Steven W. Allen, Eric D. Miller, Tanmoy Chattopadhyay | Summary: Traditional cosmic ray filtering algorithms used in X-ray imaging detectors aboard space telescopes perform event reconstruction based on the properties of activated pixels above a certain energy threshold, within 3×3 or 5×5 pixel […]


Continue.. Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Posted by dbos Stanford

Kavli Affiliate: Sven Herrmann | First 5 Authors: Artem Poliszczuk, Dan Wilkins, Steven W. Allen, Eric D. Miller, Tanmoy Chattopadhyay | Summary: Traditional cosmic ray filtering algorithms used in X-ray imaging detectors aboard space telescopes perform event reconstruction based on the properties of activated pixels above a certain energy threshold, within 3×3 or 5×5 pixel […]


Continue.. Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Posted by dbos MIT

Kavli Affiliate: Eric D. Miller | First 5 Authors: Artem Poliszczuk, Dan Wilkins, Steven W. Allen, Eric D. Miller, Tanmoy Chattopadhyay | Summary: Traditional cosmic ray filtering algorithms used in X-ray imaging detectors aboard space telescopes perform event reconstruction based on the properties of activated pixels above a certain energy threshold, within 3×3 or 5×5 […]


Continue.. Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Posted by dbos MIT

Kavli Affiliate: Catherine E. Grant | First 5 Authors: Artem Poliszczuk, Dan Wilkins, Steven W. Allen, Eric D. Miller, Tanmoy Chattopadhyay | Summary: Traditional cosmic ray filtering algorithms used in X-ray imaging detectors aboard space telescopes perform event reconstruction based on the properties of activated pixels above a certain energy threshold, within 3×3 or 5×5 […]


Continue.. Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Posted by dbos Stanford

Kavli Affiliate: Sven Herrmann | First 5 Authors: Artem Poliszczuk, Dan Wilkins, Steven W. Allen, Eric D. Miller, Tanmoy Chattopadhyay | Summary: Traditional cosmic ray filtering algorithms used in X-ray imaging detectors aboard space telescopes perform event reconstruction based on the properties of activated pixels above a certain energy threshold, within 3×3 or 5×5 pixel […]


Continue.. Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Posted by dbos MIT

Kavli Affiliate: Catherine E. Grant | First 5 Authors: Artem Poliszczuk, Dan Wilkins, Steven W. Allen, Eric D. Miller, Tanmoy Chattopadhyay | Summary: Traditional cosmic ray filtering algorithms used in X-ray imaging detectors aboard space telescopes perform event reconstruction based on the properties of activated pixels above a certain energy threshold, within 3×3 or 5×5 […]


Continue.. Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Posted by dbos MIT

Kavli Affiliate: Catherine E. Grant | First 5 Authors: Artem Poliszczuk, Dan Wilkins, Steven W. Allen, Eric D. Miller, Tanmoy Chattopadhyay | Summary: Traditional cosmic ray filtering algorithms used in X-ray imaging detectors aboard space telescopes perform event reconstruction based on the properties of activated pixels above a certain energy threshold, within 3×3 or 5×5 […]


Continue.. Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Posted by dbos MIT

Kavli Affiliate: Catherine E. Grant | First 5 Authors: Artem Poliszczuk, Dan Wilkins, Steven W. Allen, Eric D. Miller, Tanmoy Chattopadhyay | Summary: Traditional cosmic ray filtering algorithms used in X-ray imaging detectors aboard space telescopes perform event reconstruction based on the properties of activated pixels above a certain energy threshold, within 3×3 or 5×5 […]


Continue.. Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness

Posted by dbos MIT

Kavli Affiliate: Catherine E. Grant | First 5 Authors: Artem Poliszczuk, Dan Wilkins, Steven W. Allen, Eric D. Miller, Tanmoy Chattopadhyay | Summary: Traditional cosmic ray filtering algorithms used in X-ray imaging detectors aboard space telescopes perform event reconstruction based on the properties of activated pixels above a certain energy threshold, within 3×3 or 5×5 […]


Continue.. Towards efficient machine-learning-based reduction of the cosmic-ray induced background in X-ray imaging detectors: increasing context awareness