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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2306.17667 |
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| _version_ | 1866910380632047616 |
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| author | Diehl, Johannes Knollmüller, Jakob Schulz, Oliver |
| author_facet | Diehl, Johannes Knollmüller, Jakob Schulz, Oliver |
| contents | We present a method for obtaining unbiased signal estimates in the presence of a significant unknown background, eliminating the need for a parametric model for the background itself. Our approach is based on a minimal set of conditions for observation and background estimators, which are typically satisfied in practical scenarios. To showcase the effectiveness of our method, we apply it to simulated data from the planned dielectric axion haloscope MADMAX. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_17667 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Bias-Free Estimation of Signals on Top of Unknown Backgrounds Diehl, Johannes Knollmüller, Jakob Schulz, Oliver Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics High Energy Physics - Experiment Applications Methodology We present a method for obtaining unbiased signal estimates in the presence of a significant unknown background, eliminating the need for a parametric model for the background itself. Our approach is based on a minimal set of conditions for observation and background estimators, which are typically satisfied in practical scenarios. To showcase the effectiveness of our method, we apply it to simulated data from the planned dielectric axion haloscope MADMAX. |
| title | Bias-Free Estimation of Signals on Top of Unknown Backgrounds |
| topic | Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics High Energy Physics - Experiment Applications Methodology |
| url | https://arxiv.org/abs/2306.17667 |