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N. Christensen

4 papers hereh-index 218 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • astro-ph.IM2
  • gr-qc2
same name
  • N. Christensen — 116 papers, h 100
  • N. Christensen — 45 papers
  • N. Christensen — 38 papers, h 13
  • N. Christensen — 23 papers, h 26
  • N. Christensen — 9 papers, h 20
  • N. Christensen — 5 papers, h 47

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators

4 papers

astro-ph.IM2026

LIGO Detector Characterization in the Second and Third Parts of the Fourth Observing Run

J. Glanzer, A. F. Helmling-Cornell, A. Calafat +244

LIGO detector characterization efforts enabled the confident detection of gravitational waves from hundreds of compact binary coalescences during the fourth observing run. Reliable…

astro-ph.IM2026

Narrow spectral artifact investigation and mitigation in LIGO data from the fourth LIGO-Virgo-KAGRA observing run

E. Goetz, A. Neunzert, A. M. Knee +258

We present efforts to identify, characterize, and mitigate narrow spectral artifacts in LIGO detector data during the fourth LIGO-Virgo-KAGRA observing run. Narrow spectral artifac…

gr-qc2025

Coherent injection of magnetic noise and its impact on gravitational-wave searches

Kamiel Janssens, Jessica Lawrence, Anamaria Effler +11

Correlated noise sources, particularly magnetic noise, form a risk to future gravitational-wave searches aimed at detecting the gravitational-wave background. Potential noise conta…

gr-qc2024

Application of Non-Linear Noise Regression in the Virgo Detector

R. Weizmann Kiendrebeogo, Muhammed Saleem, Marie Anne Bizouard +8

This work presents the first demonstration of non-linear noise regression in the Virgo detector using deep learning techniques. We use DeepClean, a convolutional autoencoder previo…

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