Lippmann-Schwinger-Lanczos algorithm for inverse scattering problems with unknown reflectivity and loss distributions: One-dimensional Case Article Swipe
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· 2025
· Open Access
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We consider one-dimensional inverse scattering in attenuating media where both the reflectivity and loss distributions are unknown. Mathematically, this corresponds to recovering the coefficients of a damped wave operator, or equivalently, a quadratic operator pencil in the frequency domain. The Lippmann-Schwinger equation maps the unknown reflectivity and loss distribution to the measured scattered data. This mapping is nonlinear, as it requires knowledge of the internal wavefield, which itself depends on the reflectivity and loss distribution. The Lippmann-Schwinger-Lanczos method addresses this nonlinearity by approximating the internal solutions through the lifting of states from a reduced-order model constructed directly from the measured data. In this work, we extend the method to dissipative problems, enabling the approximation of internal partial differential equation (PDE) solutions in media with both reflectivity and loss distributions. We present two complementary constructions of such internal solutions: one based on spectral data and another on frequency-domain measurements over a finite interval. This development establishes a direct link between data-driven reduced-order models for inverse problems and port-Hamiltonian dynamical systems, with reduced models obtained either from the associated spectral measure or via rational approximation. Compared to the Born approximation, which replaces the internal field with the background field, our approach yields more accurate internal reconstructions and enables faster and more robust recovery of the contrast as evidenced by our numerical experiments.
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- article
- Landing Page
- http://arxiv.org/abs/2511.15058
- https://arxiv.org/pdf/2511.15058
- OA Status
- green
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- https://openalex.org/W7106477226
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https://openalex.org/W7106477226Canonical identifier for this work in OpenAlex
- Title
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Lippmann-Schwinger-Lanczos algorithm for inverse scattering problems with unknown reflectivity and loss distributions: One-dimensional CaseWork title
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articleOpenAlex work type
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2025Year of publication
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2025-11-19Full publication date if available
- Authors
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Zimmerling, Jörn, Zaslavsky, Mikhail, Mamonov, Alexander V., Druskin, Vladimir, Abilgazy, AnarzhanList of authors in order
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https://arxiv.org/abs/2511.15058Publisher landing page
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https://arxiv.org/pdf/2511.15058Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2511.15058Direct OA link when available
- Concepts
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Inverse scattering problem, Inverse problem, Mathematics, Measure (data warehouse), Inverse, Quadratic equation, Scattering, Dissipative system, Reflectivity, Mathematical analysis, Operator (biology), Field (mathematics), Algorithm, Distribution (mathematics), Nonlinear system, Optics, Reflection (computer programming), Spectral power distribution, Born approximation, Physics, Partial differential equation, Inversion (geology), Internal wave, Scattering theoryTop concepts (fields/topics) attached by OpenAlex
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| abstract_inverted_index.scattering | 4 |
| abstract_inverted_index.solutions: | 137 |
| abstract_inverted_index.wavefield, | 65 |
| abstract_inverted_index.attenuating | 6 |
| abstract_inverted_index.constructed | 95 |
| abstract_inverted_index.corresponds | 19 |
| abstract_inverted_index.data-driven | 159 |
| abstract_inverted_index.development | 153 |
| abstract_inverted_index.dissipative | 109 |
| abstract_inverted_index.establishes | 154 |
| abstract_inverted_index.coefficients | 23 |
| abstract_inverted_index.differential | 117 |
| abstract_inverted_index.distribution | 48 |
| abstract_inverted_index.experiments. | 219 |
| abstract_inverted_index.measurements | 147 |
| abstract_inverted_index.nonlinearity | 80 |
| abstract_inverted_index.reflectivity | 11, 45, 71, 125 |
| abstract_inverted_index.approximating | 82 |
| abstract_inverted_index.approximation | 113 |
| abstract_inverted_index.complementary | 132 |
| abstract_inverted_index.constructions | 133 |
| abstract_inverted_index.distribution. | 74 |
| abstract_inverted_index.distributions | 14 |
| abstract_inverted_index.equivalently, | 30 |
| abstract_inverted_index.reduced-order | 93, 160 |
| abstract_inverted_index.approximation, | 187 |
| abstract_inverted_index.approximation. | 182 |
| abstract_inverted_index.distributions. | 128 |
| abstract_inverted_index.Mathematically, | 17 |
| abstract_inverted_index.one-dimensional | 2 |
| abstract_inverted_index.reconstructions | 203 |
| abstract_inverted_index.frequency-domain | 146 |
| abstract_inverted_index.port-Hamiltonian | 166 |
| abstract_inverted_index.Lippmann-Schwinger | 40 |
| abstract_inverted_index.Lippmann-Schwinger-Lanczos | 76 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.84233857 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |