Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:47:49.035961Z
Paper Citation Record · LEDGER
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications
As of 24 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2506.01559.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
31 of 31 outbound references displayed
- verified exact1
- verified fuzzy23
- unresolved7
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation dba823ea-86d4-48eb-b0e4-b061a27d8b82 · outbound
This paper cites Highly accurate protein structure prediction with alphafold.nature, 596(7873):583–589, 2021.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Highly accurate protein structure prediction with alphafold.nature, 596(7873):583–589, 2021
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:48:04.254894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f7634621-5533-4705-91cd-357e42fda652 · outbound
This paper cites Predicting multiple conformations via sequence clustering and alphafold2.Nature, 625(7996):832–839, 2024.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Predicting multiple conformations via sequence clustering and alphafold2.Nature, 625(7996):832–839, 2024
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:52.213148Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 88839be1-c938-4e92-a067-b7bf781de3f0 · outbound
This paper cites A gen- eral method applicable to the search for similarities in the amino acid sequence of two proteins.Journal of molecular biology, 48(3):443–453, 1970.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications A gen- eral method applicable to the search for similarities in the amino acid sequence of two proteins.Journal of molecular biology, 48(3):443–453, 1970
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:46:59.745870Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ab978d0f-fac3-4b6f-be41-bea78687654a · outbound
This paper cites On the complexity of 12 multiple sequence alignment.Journal of computational biology, 1(4):337–348, 1994.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications On the complexity of 12 multiple sequence alignment.Journal of computational biology, 1(4):337–348, 1994
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:52.083635Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1d4ed1b4-8f38-43af-82ce-6740aaa86594 · outbound
This paper cites Multiple sequence alignment with hierarchical clustering.Nucleic acids research, 16(22):10881–10890, 1988.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Multiple sequence alignment with hierarchical clustering.Nucleic acids research, 16(22):10881–10890, 1988
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:52.015848Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7eb70d14-21a7-4984-b79e-b3aefcd049f0 · outbound
This paper cites T-coffee: A novel method for fast and accu- rate multiple sequence alignment.Journal of molecular biology, 302(1):205–217, 2000.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications T-coffee: A novel method for fast and accu- rate multiple sequence alignment.Journal of molecular biology, 302(1):205–217, 2000
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:51.935528Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation be08f6a0-3f76-4f4a-aa75-39dfde71c063 · outbound
This paper cites Hm- mer web server: interactive sequence similarity search- ing.Nucleic acids research, 39(suppl 2):W29–W37, 2011.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Hm- mer web server: interactive sequence similarity search- ing.Nucleic acids research, 39(suppl 2):W29–W37, 2011
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:51.879330Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2f777ce5-64d4-474c-b49e-7acabdb0ed1c · outbound
This paper cites A site- resolved two-dimensional quantum simulator with hun- dreds of trapped ions.Nature, pages 1–6, 2024.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications A site- resolved two-dimensional quantum simulator with hun- dreds of trapped ions.Nature, pages 1–6, 2024
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:51.811551Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 95cd034e-017e-48a5-b882-1186d56a007b · outbound
This paper cites Quantum supremacy using a programmable supercon- ducting processor.Nature, 574(7779):505–510, 2019.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Quantum supremacy using a programmable supercon- ducting processor.Nature, 574(7779):505–510, 2019
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:46:59.999679Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6136e08b-48ab-4aa6-96e2-9cd478b1837b · outbound
This paper cites Quan- tum computational advantage using photons.Science, 370(6523):1460–1463, 2020.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Quan- tum computational advantage using photons.Science, 370(6523):1460–1463, 2020
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:51.659946Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1671f71f-fbac-4058-8ebb-c5ea1d63ff85 · outbound
This paper cites Quantum error correction below the surface code threshold.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Quantum error correction below the surface code threshold
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:47:00.065731Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d8b24c85-1399-459a-bfc1-70adc597b768 · outbound
This paper cites Genome assembly using quantum and quantum-inspired annealing.Scientific Reports, 11(1):13183, 2021.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Genome assembly using quantum and quantum-inspired annealing.Scientific Reports, 11(1):13183, 2021
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:51.487824Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 744964bb-42ea-4eb5-9c51-25570e3b11ac · outbound
This paper cites Finding low-energy conformations of lattice protein models by quantum annealing.Scientific reports, 2(1):1–7, 2012.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Finding low-energy conformations of lattice protein models by quantum annealing.Scientific reports, 2(1):1–7, 2012
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:51.261149Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation cec95ae6-f5f0-46cf-89ec-7a0c879526af · outbound
This paper cites Resource-efficient quantum algorithm for protein folding.npj Quantum Informa- tion, 7(1):38, 2021.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Resource-efficient quantum algorithm for protein folding.npj Quantum Informa- tion, 7(1):38, 2021
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:51.088592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7d803aea-c866-4bfd-ada2-c7b96b524006 · outbound
This paper cites Quantum computational quantification of protein-ligand interactions.Interna- tional Journal of Quantum Chemistry, 122(22):e26975, 2022.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Quantum computational quantification of protein-ligand interactions.Interna- tional Journal of Quantum Chemistry, 122(22):e26975, 2022
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:50.938901Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d64d8311-d14f-4115-bb83-7ec275850f88 · outbound
This paper cites Encoding molecular docking for quantum com- puters.Journal of Chemical Theory and Computation, 19(24):9018–9024, 2023.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Encoding molecular docking for quantum com- puters.Journal of Chemical Theory and Computation, 19(24):9018–9024, 2023
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:50.864963Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation cdec77f7-2fcb-4c3d-8a7c-79422c266736 · outbound
This paper cites Exploring the advantages of quantum generative adversarial networks in generative chemistry.Journal of Chemical Information and Modeling, 63(11):3307–3318, 2023.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Exploring the advantages of quantum generative adversarial networks in generative chemistry.Journal of Chemical Information and Modeling, 63(11):3307–3318, 2023
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:47:00.306432Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8dcfb4e0-9d02-452b-a936-73f8847a1da2 · outbound
This paper cites Quantum Computing-Enhanced Algorithm Unveils Novel Inhibitors for KRAS.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Quantum Computing-Enhanced Algorithm Unveils Novel Inhibitors for KRAS
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:47:00.341656Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 91de9c69-5d4f-4643-8e6a-1f4ce51a2c8d · outbound
This paper cites Quantum bridge analytics i: a tutorial on for- mulating and using qubo models.Annals of Operations Research, 314(1):141–183, 2022.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Quantum bridge analytics i: a tutorial on for- mulating and using qubo models.Annals of Operations Research, 314(1):141–183, 2022
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:50.761057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation abf262a8-f660-4e48-a369-d76607c20afb · outbound
This paper cites Quaser: Quantum accelerated de novo dna sequence reconstruc- tion.Plos one, 16(4):e0249850, 2021.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Quaser: Quantum accelerated de novo dna sequence reconstruc- tion.Plos one, 16(4):e0249850, 2021
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:50.668740Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation ad467fbb-51df-4f51-8e66-25e483bede6b · outbound
This paper cites Multi-sequence alignment using the Quantum Approximate Optimization Algorithm.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Multi-sequence alignment using the Quantum Approximate Optimization Algorithm
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:47:49.663113Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d4dbc935-7025-4ac6-af33-eee97b0710c7 · outbound
This paper cites Improv- ing variational quantum optimization using cvar.Quan- tum, 4:256, 2020.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Improv- ing variational quantum optimization using cvar.Quan- tum, 4:256, 2020
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:50.586783Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 72545aac-e760-4873-b8e2-0eea2c22fa41 · outbound
This paper cites Accurate prediction of protein structures and in- teractions using a three-track neural network.Science, 373(6557):871–876, 2021.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Accurate prediction of protein structures and in- teractions using a three-track neural network.Science, 373(6557):871–876, 2021
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:50.492315Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1b6faaf0-41a2-4dcb-931d-c6a477486f13 · outbound
This paper cites Evolutionary- scale prediction of atomic-level protein structure with a language model.Science, 379(6637):1123–1130, 2023.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Evolutionary- scale prediction of atomic-level protein structure with a language model.Science, 379(6637):1123–1130, 2023
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:47:00.600777Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 159dffe0-a14c-4509-97e3-824895af4f45 · outbound
This paper cites Encoding patterns for quantum algo- rithms.IET Quantum Communication, 2(4):141–152, 2021.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Encoding patterns for quantum algo- rithms.IET Quantum Communication, 2(4):141–152, 2021
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:50.407890Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 540cb20a-3b8b-4b29-bd32-d8e2e531eee4 · outbound
This paper cites Realizing coherently convertible dual-type qubits with the same ion species.Nature Physics, 18(9):1058–1061, 2022.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Realizing coherently convertible dual-type qubits with the same ion species.Nature Physics, 18(9):1058–1061, 2022
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:50.310978Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f2fa125f-f572-4631-87ed-35d914fafb30 · outbound
This paper cites Scalable hyperfine qubit state detection via electron shelving in the 2 d 5/2 and 2 f 7/2 manifolds in 171 yb+.Physical Review A, 104(1):012606, 2021.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Scalable hyperfine qubit state detection via electron shelving in the 2 d 5/2 and 2 f 7/2 manifolds in 171 yb+.Physical Review A, 104(1):012606, 2021
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:50.206353Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation cc4418bd-6110-472c-823e-59619d400648 · outbound
This paper cites q-coding.hyqubit.com.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications q-coding.hyqubit.com
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:50.074741Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c0ef6f3e-4999-44c4-a9d8-ccd68cc6b6bd · outbound
This paper cites an unresolved cited work.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Unresolved cited work
Reference 29
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:47:49.940184Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c6a5274d-ab1b-42c9-9247-d4184b9bfc64 · outbound
This paper cites Quantumnas: Noise-adaptive search for robust quantum circuits.
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Quantumnas: Noise-adaptive search for robust quantum circuits
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:47:49.810469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation df060a70-7472-40b8-8140-17806bf3193b · outbound
This paper cites Both scenarios were solved using a HEA circuit that employed 20 qubits and two layers (see Appendix A for details).
hqQUBO: A Hybrid-querying Quantum Optimization Model Validated with 16-qubits on an Ion Trap Quantum Computer for Life Science Applications Both scenarios were solved using a HEA circuit that employed 20 qubits and two layers (see Appendix A for details)
Reference 3060
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:48:04.277701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Pith citing papers
No inbound Pith citation observations are available.