Inverse design for robust inference in integrated computational spectrometry Article Swipe
Wenchao Ma
,
Raphaël Pestourie
,
Zin Lin
,
Steven G. Johnson
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2506.02194
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2506.02194
We propose an inverse-design approach for computational spectrometers in which the scattering media are topology-optimized to achieve better performance in inference of unknown spectra. Unlike traditional end-to-end approaches, our inverse design of the scattering media does not need a training set of spectra, a distribution of detector noise, or an inference algorithm. Our approach allows the selection of the inference algorithm to be decoupled from that of the scatterer. For smooth spectra, we additionally devise a regularized reconstruction algorithm based on Chebyshev interpolation, which yields higher accuracy compared with conventional methods in which the spectra are sampled at equally spaced frequencies or wavelengths with equal weights. Our approaches are numerically demonstrated via inverse design of integrated computational spectrometers and reconstruction of example spectra. The inverse-designed spectrometers exhibit significantly better performance in the presence of noise than their counterparts with random scatterers. Our method provides a useful complement to end-to-end co-design methods.
Related Topics
Concepts
No concepts available.
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2506.02194
- https://arxiv.org/pdf/2506.02194
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W4415130755
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4415130755Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2506.02194Digital Object Identifier
- Title
-
Inverse design for robust inference in integrated computational spectrometryWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-06-02Full publication date if available
- Authors
-
Wenchao Ma, Raphaël Pestourie, Zin Lin, Steven G. JohnsonList of authors in order
- Landing page
-
https://arxiv.org/abs/2506.02194Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2506.02194Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2506.02194Direct OA link when available
- Cited by
-
0Total citation count in OpenAlex
Full payload
| id | https://openalex.org/W4415130755 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2506.02194 |
| ids.doi | https://doi.org/10.48550/arxiv.2506.02194 |
| ids.openalex | https://openalex.org/W4415130755 |
| fwci | |
| type | preprint |
| title | Inverse design for robust inference in integrated computational spectrometry |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10640 |
| topics[0].field.id | https://openalex.org/fields/16 |
| topics[0].field.display_name | Chemistry |
| topics[0].score | 0.9606000185012817 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1602 |
| topics[0].subfield.display_name | Analytical Chemistry |
| topics[0].display_name | Spectroscopy and Chemometric Analyses |
| topics[1].id | https://openalex.org/T10876 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.949999988079071 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2207 |
| topics[1].subfield.display_name | Control and Systems Engineering |
| topics[1].display_name | Fault Detection and Control Systems |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2506.02194 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2506.02194 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | text |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2506.02194 |
| locations[1].id | doi:10.48550/arxiv.2506.02194 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://doi.org/10.48550/arxiv.2506.02194 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5017519155 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-3895-5163 |
| authorships[0].author.display_name | Wenchao Ma |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Ma, Wenchao |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5041370077 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-6267-8771 |
| authorships[1].author.display_name | Raphaël Pestourie |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Pestourie, Raphaël |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5101697374 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-1219-0932 |
| authorships[2].author.display_name | Zin Lin |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Lin, Zin |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5087662980 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-7327-4967 |
| authorships[3].author.display_name | Steven G. Johnson |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Johnson, Steven G. |
| authorships[3].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2506.02194 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-14T00:00:00 |
| display_name | Inverse design for robust inference in integrated computational spectrometry |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T10640 |
| primary_topic.field.id | https://openalex.org/fields/16 |
| primary_topic.field.display_name | Chemistry |
| primary_topic.score | 0.9606000185012817 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1602 |
| primary_topic.subfield.display_name | Analytical Chemistry |
| primary_topic.display_name | Spectroscopy and Chemometric Analyses |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:2506.02194 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/2506.02194 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2506.02194 |
| primary_location.id | pmh:oai:arXiv.org:2506.02194 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2506.02194 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2506.02194 |
| publication_date | 2025-06-02 |
| publication_year | 2025 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 38, 43, 75, 144 |
| abstract_inverted_index.We | 0 |
| abstract_inverted_index.an | 2, 49 |
| abstract_inverted_index.at | 97 |
| abstract_inverted_index.be | 62 |
| abstract_inverted_index.in | 8, 19, 91, 130 |
| abstract_inverted_index.of | 21, 31, 41, 45, 57, 66, 114, 120, 133 |
| abstract_inverted_index.on | 80 |
| abstract_inverted_index.or | 48, 101 |
| abstract_inverted_index.to | 15, 61, 147 |
| abstract_inverted_index.we | 72 |
| abstract_inverted_index.For | 69 |
| abstract_inverted_index.Our | 52, 106, 141 |
| abstract_inverted_index.The | 123 |
| abstract_inverted_index.and | 118 |
| abstract_inverted_index.are | 13, 95, 108 |
| abstract_inverted_index.for | 5 |
| abstract_inverted_index.not | 36 |
| abstract_inverted_index.our | 28 |
| abstract_inverted_index.set | 40 |
| abstract_inverted_index.the | 10, 32, 55, 58, 67, 93, 131 |
| abstract_inverted_index.via | 111 |
| abstract_inverted_index.does | 35 |
| abstract_inverted_index.from | 64 |
| abstract_inverted_index.need | 37 |
| abstract_inverted_index.than | 135 |
| abstract_inverted_index.that | 65 |
| abstract_inverted_index.with | 88, 103, 138 |
| abstract_inverted_index.based | 79 |
| abstract_inverted_index.equal | 104 |
| abstract_inverted_index.media | 12, 34 |
| abstract_inverted_index.noise | 134 |
| abstract_inverted_index.their | 136 |
| abstract_inverted_index.which | 9, 83, 92 |
| abstract_inverted_index.Unlike | 24 |
| abstract_inverted_index.allows | 54 |
| abstract_inverted_index.better | 17, 128 |
| abstract_inverted_index.design | 30, 113 |
| abstract_inverted_index.devise | 74 |
| abstract_inverted_index.higher | 85 |
| abstract_inverted_index.method | 142 |
| abstract_inverted_index.noise, | 47 |
| abstract_inverted_index.random | 139 |
| abstract_inverted_index.smooth | 70 |
| abstract_inverted_index.spaced | 99 |
| abstract_inverted_index.useful | 145 |
| abstract_inverted_index.yields | 84 |
| abstract_inverted_index.achieve | 16 |
| abstract_inverted_index.equally | 98 |
| abstract_inverted_index.example | 121 |
| abstract_inverted_index.exhibit | 126 |
| abstract_inverted_index.inverse | 29, 112 |
| abstract_inverted_index.methods | 90 |
| abstract_inverted_index.propose | 1 |
| abstract_inverted_index.sampled | 96 |
| abstract_inverted_index.spectra | 94 |
| abstract_inverted_index.unknown | 22 |
| abstract_inverted_index.accuracy | 86 |
| abstract_inverted_index.approach | 4, 53 |
| abstract_inverted_index.compared | 87 |
| abstract_inverted_index.detector | 46 |
| abstract_inverted_index.methods. | 150 |
| abstract_inverted_index.presence | 132 |
| abstract_inverted_index.provides | 143 |
| abstract_inverted_index.spectra, | 42, 71 |
| abstract_inverted_index.spectra. | 23, 122 |
| abstract_inverted_index.training | 39 |
| abstract_inverted_index.weights. | 105 |
| abstract_inverted_index.Chebyshev | 81 |
| abstract_inverted_index.algorithm | 60, 78 |
| abstract_inverted_index.co-design | 149 |
| abstract_inverted_index.decoupled | 63 |
| abstract_inverted_index.inference | 20, 50, 59 |
| abstract_inverted_index.selection | 56 |
| abstract_inverted_index.algorithm. | 51 |
| abstract_inverted_index.approaches | 107 |
| abstract_inverted_index.complement | 146 |
| abstract_inverted_index.end-to-end | 26, 148 |
| abstract_inverted_index.integrated | 115 |
| abstract_inverted_index.scatterer. | 68 |
| abstract_inverted_index.scattering | 11, 33 |
| abstract_inverted_index.approaches, | 27 |
| abstract_inverted_index.frequencies | 100 |
| abstract_inverted_index.numerically | 109 |
| abstract_inverted_index.performance | 18, 129 |
| abstract_inverted_index.regularized | 76 |
| abstract_inverted_index.scatterers. | 140 |
| abstract_inverted_index.traditional | 25 |
| abstract_inverted_index.wavelengths | 102 |
| abstract_inverted_index.additionally | 73 |
| abstract_inverted_index.conventional | 89 |
| abstract_inverted_index.counterparts | 137 |
| abstract_inverted_index.demonstrated | 110 |
| abstract_inverted_index.distribution | 44 |
| abstract_inverted_index.computational | 6, 116 |
| abstract_inverted_index.significantly | 127 |
| abstract_inverted_index.spectrometers | 7, 117, 125 |
| abstract_inverted_index.interpolation, | 82 |
| abstract_inverted_index.inverse-design | 3 |
| abstract_inverted_index.reconstruction | 77, 119 |
| abstract_inverted_index.inverse-designed | 124 |
| abstract_inverted_index.topology-optimized | 14 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile |