Compensator-Based Inference for Signal Detection Under Unknown Background
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866910239312314368 |
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| author | Banerjee, Aritra Algeri, Sara |
| author_facet | Banerjee, Aritra Algeri, Sara |
| contents | The problem of detecting new signals in the presence of an unknown background is ubiquitous in scientific discoveries and is especially prominent in the physical sciences. Most solutions proposed thus far to address the problem focus on estimating the background distribution and using that estimate to infer the signal. By studying the geometry of the problem, this article demonstrates that estimating the background distribution is somewhat unnecessary for inferring the signal intensity. Instead, it suffices to estimate a single parameter, referred to as the compensator, to account for the incomplete knowledge on the background, substantially simplifying the problem's complexity and enabling proper uncertainty propagation. Such a compensator is shown to govern the conservativeness of the inference, both in the proposed setup and in likelihood-based approaches. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_20508 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Compensator-Based Inference for Signal Detection Under Unknown Background Banerjee, Aritra Algeri, Sara Methodology High Energy Astrophysical Phenomena Instrumentation and Methods for Astrophysics Data Analysis, Statistics and Probability Applications The problem of detecting new signals in the presence of an unknown background is ubiquitous in scientific discoveries and is especially prominent in the physical sciences. Most solutions proposed thus far to address the problem focus on estimating the background distribution and using that estimate to infer the signal. By studying the geometry of the problem, this article demonstrates that estimating the background distribution is somewhat unnecessary for inferring the signal intensity. Instead, it suffices to estimate a single parameter, referred to as the compensator, to account for the incomplete knowledge on the background, substantially simplifying the problem's complexity and enabling proper uncertainty propagation. Such a compensator is shown to govern the conservativeness of the inference, both in the proposed setup and in likelihood-based approaches. |
| title | Compensator-Based Inference for Signal Detection Under Unknown Background |
| topic | Methodology High Energy Astrophysical Phenomena Instrumentation and Methods for Astrophysics Data Analysis, Statistics and Probability Applications |
| url | https://arxiv.org/abs/2605.20508 |