Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-19T03:17:37.583689Z
Paper Citation Record · LEDGER
Optimizing quantum sensing networks via genetic algorithms and deep learning
As of 16 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2507.17460.
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 2026-08-16T06:30:59.297886+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
60 of 60 outbound references displayed
- verified exact5
- verified fuzzy54
- unresolved1
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 327aa2f6-cab6-4895-a1a5-75b185239b6a · outbound
This paper cites The total transverse magnetization operator is defined as Mx = N ∑ i=1 σx i , (12) where σx i is the Pauli X operator acting on site i.
Optimizing quantum sensing networks via genetic algorithms and deep learning The total transverse magnetization operator is defined as Mx = N ∑ i=1 σx i , (12) where σx i is the Pauli X operator acting on site i
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.124809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 03345a80-fe98-42e3-85bc-59e95478e276 · outbound
This paper cites We consider both Kac scaling intro- duces a normalization of the interaction strength by the sys- tem size, setting the effective coupling to Jeff = J/2N.
Optimizing quantum sensing networks via genetic algorithms and deep learning We consider both Kac scaling intro- duces a normalization of the interaction strength by the sys- tem size, setting the effective coupling to Jeff = J/2N
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.074789Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1a41425b-881e-4fe1-9938-e42c8bae12dc · outbound
This paper cites an unresolved cited work.
Optimizing quantum sensing networks via genetic algorithms and deep learning Unresolved cited work
Reference 3
- Resolution
- unresolved
- raw_fallback, observed 2026-05-19T03:22:58.134768Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d5813b58-5271-485b-9154-89aa2e5d8419 · outbound
This paper cites Quantum sens- ing.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum sens- ing
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.129714Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 354ceba4-262d-464e-b4db-7c5bd61969db · outbound
This paper cites Ad- vances in quantum metrology.
Optimizing quantum sensing networks via genetic algorithms and deep learning Ad- vances in quantum metrology
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.112634Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 527a2881-ae40-47e1-b5eb-c9308066cecb · outbound
This paper cites Quantum metrology.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum metrology
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.102549Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 204e6e56-7aaa-4329-83a2-f22423474067 · outbound
This paper cites Coherence in quantum es- timation.
Optimizing quantum sensing networks via genetic algorithms and deep learning Coherence in quantum es- timation
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.107832Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation bc09c992-4321-40c3-bb3f-76131ceaf5ec · outbound
This paper cites Bath-induced correlations enhance ther- mometry precision at low temperatures.
Optimizing quantum sensing networks via genetic algorithms and deep learning Bath-induced correlations enhance ther- mometry precision at low temperatures
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.092435Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e3534b6e-a7e1-42d8-b75b-7bac7d12ddd0 · outbound
This paper cites Scalable spin squeezing for quantum- enhanced magnetometry with bose-einstein condensates.
Optimizing quantum sensing networks via genetic algorithms and deep learning Scalable spin squeezing for quantum- enhanced magnetometry with bose-einstein condensates
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.071357Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation da975892-e23d-40f2-8e9c-6364c077a52b · outbound
This paper cites Low-temperature quantum thermometry boosted by coherence generation.
Optimizing quantum sensing networks via genetic algorithms and deep learning Low-temperature quantum thermometry boosted by coherence generation
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.088766Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9de617e1-5bb3-4866-a038-c82f003514fc · outbound
This paper cites Review: Quantum metrology and sensing with many-body systems.
Optimizing quantum sensing networks via genetic algorithms and deep learning Review: Quantum metrology and sensing with many-body systems
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.104070Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 82140e6a-b43c-42bd-a515-3a57b05a7940 · outbound
This paper cites Current trends in global quantum metrology.
Optimizing quantum sensing networks via genetic algorithms and deep learning Current trends in global quantum metrology
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.082647Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2dbad466-a13f-4774-9908-3a20f3e1b31b · outbound
This paper cites Improved quantum magnetometry beyond the standard quantum limit.
Optimizing quantum sensing networks via genetic algorithms and deep learning Improved quantum magnetometry beyond the standard quantum limit
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.137519Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 33da9f49-496c-4c92-82d1-436696ae844f · outbound
This paper cites Lattice quantum magnetometry.
Optimizing quantum sensing networks via genetic algorithms and deep learning Lattice quantum magnetometry
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.127537Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 21323033-15da-41e0-bac3-18aedde0cc98 · outbound
This paper cites Quantum noise limited and entanglement-assisted magnetometry.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum noise limited and entanglement-assisted magnetometry
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.140215Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 12a0dfa3-a4f4-4260-ba3c-e337a5fb9107 · outbound
This paper cites Quantum magne- tometry using discrete-time quantum walk.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum magne- tometry using discrete-time quantum walk
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.090765Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fb59c61a-fb93-433b-8eec-ddf1513928ab · outbound
This paper cites Universal quantum magnetometry with spin states at equilibrium.
Optimizing quantum sensing networks via genetic algorithms and deep learning Universal quantum magnetometry with spin states at equilibrium
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.034010Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9a2d2230-9492-49b4-adb8-5915f53c9aa1 · outbound
This paper cites Ultimate limits for quantum magnetometry via time-continuous measurements.
Optimizing quantum sensing networks via genetic algorithms and deep learning Ultimate limits for quantum magnetometry via time-continuous measurements
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:57.991639Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f0b55228-8a3c-404f-8e1e-ae5971f70d2f · outbound
This paper cites Sequential measurements for quantum- enhanced magnetometry in spin chain probes.
Optimizing quantum sensing networks via genetic algorithms and deep learning Sequential measurements for quantum- enhanced magnetometry in spin chain probes
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.119365Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5b6a3fa5-8c4b-4906-b7c8-228aa2187e32 · outbound
This paper cites Quantum-enhanced magne- tometry by phase estimation algorithms with a single artificial atom.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum-enhanced magne- tometry by phase estimation algorithms with a single artificial atom
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.116823Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 867e997d-b1ea-4d07-b1cb-5fb2c480b4cb · outbound
This paper cites Ultrasensitive magnetometer using a single atom.
Optimizing quantum sensing networks via genetic algorithms and deep learning Ultrasensitive magnetometer using a single atom
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.058446Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 87ee9735-59ad-420a-b439-20a9177e4d04 · outbound
This paper cites Smooth optimal quantum control for robust solid-state spin magnetometry.
Optimizing quantum sensing networks via genetic algorithms and deep learning Smooth optimal quantum control for robust solid-state spin magnetometry
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.111651Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f5d0cb00-2476-4096-b531-c16887166319 · outbound
This paper cites Sub-projection-noise sensitivity in broadband atomic magnetometry.
Optimizing quantum sensing networks via genetic algorithms and deep learning Sub-projection-noise sensitivity in broadband atomic magnetometry
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:57.948548Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3a33927e-b33a-4d3a-9880-250c2412633f · outbound
This paper cites Magnetic sensitivity beyond the projection noise limit by spin squeezing.
Optimizing quantum sensing networks via genetic algorithms and deep learning Magnetic sensitivity beyond the projection noise limit by spin squeezing
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.079527Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 59cdd6c1-e8d8-4cae-8f4c-d75335602971 · outbound
This paper cites Quantum metrology with a scanning probe atom interferometer.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum metrology with a scanning probe atom interferometer
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.114036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a3f763ff-a788-4971-8952-b3cbd56753fd · outbound
This paper cites Subfemtotesla scalar atomic magnetometry using multipass cells.
Optimizing quantum sensing networks via genetic algorithms and deep learning Subfemtotesla scalar atomic magnetometry using multipass cells
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:57.968933Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 17b8e65e-6b8d-4e4c-aa76-4448ece0d434 · outbound
This paper cites Shot-noise-limited magnetometer with sub-picotesla sensitivity at room temperature.
Optimizing quantum sensing networks via genetic algorithms and deep learning Shot-noise-limited magnetometer with sub-picotesla sensitivity at room temperature
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.131947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7e0df961-555f-4342-964c-7a71d3cfe9ce · outbound
This paper cites Quantum critical metrology.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum critical metrology
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:57.975572Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 959a9866-590c-454d-a281-e4d7acd2c486 · outbound
This paper cites Critical quantum metrology with a finite- component quantum phase transition.
Optimizing quantum sensing networks via genetic algorithms and deep learning Critical quantum metrology with a finite- component quantum phase transition
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.101325Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8814232a-052d-429c-ad53-8b9721af4047 · outbound
This paper cites Quantum critical phenomena in a spin- 1 2 frus- trated square lattice with spatial anisotropy.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum critical phenomena in a spin- 1 2 frus- trated square lattice with spatial anisotropy
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.087339Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 65466b07-0f22-49c6-8f31-6d096ffa4b9b · outbound
This paper cites Multiparameter estimation in networked quantum sen- sors.
Optimizing quantum sensing networks via genetic algorithms and deep learning Multiparameter estimation in networked quantum sen- sors
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:57.978861Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5fe47d61-11ee-4a14-ae2b-79d764f33423 · outbound
This paper cites Role of topology in determining the precision of a finite thermometer.
Optimizing quantum sensing networks via genetic algorithms and deep learning Role of topology in determining the precision of a finite thermometer
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:57.958600Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 25b3053a-5624-4888-8867-026b2f6b0f53 · outbound
This paper cites Optimal thermometers with spin networks.
Optimizing quantum sensing networks via genetic algorithms and deep learning Optimal thermometers with spin networks
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.063917Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a2324ce3-774b-4790-b642-4fb0f4155def · outbound
This paper cites Stochastic colli- sion model approach to transport phenomena in quantum net- works.
Optimizing quantum sensing networks via genetic algorithms and deep learning Stochastic colli- sion model approach to transport phenomena in quantum net- works
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:57.972302Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0e1ca4b7-66be-4e94-bf13-9d75440b8749 · outbound
This paper cites Quantum trans- port efficiency in noisy random-removal and small-world net- works.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum trans- port efficiency in noisy random-removal and small-world net- works
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.083868Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4f3cc744-a278-4953-801e-0f9f8d7df72f · outbound
This paper cites Perturbed graphs achieve unit transport effi- ciency without environmental noise.
Optimizing quantum sensing networks via genetic algorithms and deep learning Perturbed graphs achieve unit transport effi- ciency without environmental noise
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.121478Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fce6c137-19f8-4cef-b13e-17312ff067e6 · outbound
This paper cites Memory preservation in highly-connected quantum networks.
Optimizing quantum sensing networks via genetic algorithms and deep learning Memory preservation in highly-connected quantum networks
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T03:22:01.243116Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c938524e-97b1-4e84-89ab-12d228bbcd4c · outbound
This paper cites Enhanced quantum transport in chiral quantum walks.
Optimizing quantum sensing networks via genetic algorithms and deep learning Enhanced quantum transport in chiral quantum walks
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.071614Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation bffd7e62-e27b-4bea-8c34-237a67cbe266 · outbound
This paper cites Ge- ometrical optimization of spin clusters for the preservation of quantum coherence.
Optimizing quantum sensing networks via genetic algorithms and deep learning Ge- ometrical optimization of spin clusters for the preservation of quantum coherence
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.061156Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f3a4da03-089b-4769-a11c-cfa5d5c80686 · outbound
This paper cites Quantum walk coherences on a dynamical percolation graph.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum walk coherences on a dynamical percolation graph
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.106920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b4874b45-b222-4966-9f45-441155c3fb5c · outbound
This paper cites Identifying network topologies via quantum walk distributions.
Optimizing quantum sensing networks via genetic algorithms and deep learning Identifying network topologies via quantum walk distributions
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.067781Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 56d7b023-c5dc-4e64-90b7-129f5536a817 · outbound
This paper cites Configuration-dependent precision in magnetometry and thermometry using multi-qubit quantum sensors.
Optimizing quantum sensing networks via genetic algorithms and deep learning Configuration-dependent precision in magnetometry and thermometry using multi-qubit quantum sensors
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T03:22:01.238979Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a278849b-ab5d-4b22-9bab-26a295d99ef9 · outbound
This paper cites Inferring quantum network topologies using genetic optimisation of indirect measurements.
Optimizing quantum sensing networks via genetic algorithms and deep learning Inferring quantum network topologies using genetic optimisation of indirect measurements
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T03:22:01.255883Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 05250ddd-cfd3-4e08-a684-c759d36ab815 · outbound
This paper cites Quantum estimation for quantum technol- ogy.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum estimation for quantum technol- ogy
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.052164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a5264e74-93f7-421a-ba3f-d71d8011b685 · outbound
This paper cites Learn- ing quantum systems.
Optimizing quantum sensing networks via genetic algorithms and deep learning Learn- ing quantum systems
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.049525Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 797d2aa2-0771-4f8a-803c-e6572e162b94 · outbound
This paper cites Neural-network-based parameter estima- tion for quantum detection.
Optimizing quantum sensing networks via genetic algorithms and deep learning Neural-network-based parameter estima- tion for quantum detection
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.046662Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 188b87ca-f5c6-461c-be9c-c67ecba94790 · outbound
This paper cites Multiclass classification of dephasing channels.
Optimizing quantum sensing networks via genetic algorithms and deep learning Multiclass classification of dephasing channels
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.043375Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b7208e28-50f3-4f30-8955-0fdf2e8c85b2 · outbound
This paper cites Enhancing quantum state tomography via resource-efficient attention-based neural net- works.
Optimizing quantum sensing networks via genetic algorithms and deep learning Enhancing quantum state tomography via resource-efficient attention-based neural net- works
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.039341Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 50a9f658-2718-4c67-9467-f986b359129e · outbound
This paper cites Multiparameter estima- tion of continuous-time quantum walk hamiltonians through machine learning.
Optimizing quantum sensing networks via genetic algorithms and deep learning Multiparameter estima- tion of continuous-time quantum walk hamiltonians through machine learning
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.023553Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9a020d2a-2792-420b-9ec1-fc383afa9aa2 · outbound
This paper cites Genetic algorithms and machine learning.
Optimizing quantum sensing networks via genetic algorithms and deep learning Genetic algorithms and machine learning
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.019674Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 166bb628-664d-4d8b-b9d3-a060b5787b78 · outbound
This paper cites Multi- objective optimization using genetic algorithms: A tutorial.
Optimizing quantum sensing networks via genetic algorithms and deep learning Multi- objective optimization using genetic algorithms: A tutorial
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.037540Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3877bec5-0c1f-40ca-a3be-1944e51ee80e · outbound
This paper cites Evolutionary Computing.
Optimizing quantum sensing networks via genetic algorithms and deep learning Evolutionary Computing
Reference 53
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T03:22:01.246970Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7b95b219-0cab-43b5-ba39-1e389ed50404 · outbound
This paper cites On the van der waals theory of the vapor-liquid equilibrium. i. discussion of a one-dimensional model.
Optimizing quantum sensing networks via genetic algorithms and deep learning On the van der waals theory of the vapor-liquid equilibrium. i. discussion of a one-dimensional model
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:57.991891Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2c90c970-2391-484a-a623-1809198ba4b5 · outbound
This paper cites Quantum fisher information for states in expo- nential form.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum fisher information for states in expo- nential form
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.076111Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 46fe5349-6577-455f-89ec-9b437381c3ab · outbound
This paper cites Quantum-enhanced measurements: Beating the standard quantum limit.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum-enhanced measurements: Beating the standard quantum limit
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.094043Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7ede7d0d-aff7-4fde-8371-8ca1e539ed53 · outbound
This paper cites At the limits of criticality- based quantum metrology: Apparent super-heisenberg scaling revisited.
Optimizing quantum sensing networks via genetic algorithms and deep learning At the limits of criticality- based quantum metrology: Apparent super-heisenberg scaling revisited
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.055211Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7789e876-3575-4bbf-ba94-fe24c914d6e8 · outbound
This paper cites Sta- tistical mechanics and dynamics of solvable models with long- range interactions.
Optimizing quantum sensing networks via genetic algorithms and deep learning Sta- tistical mechanics and dynamics of solvable models with long- range interactions
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.045023Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9ea47e3a-2e5e-414e-b3e3-9680f56495f6 · outbound
This paper cites Quantum metrology from a quantum information science perspective.
Optimizing quantum sensing networks via genetic algorithms and deep learning Quantum metrology from a quantum information science perspective
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.030580Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c62e66fe-c6e5-4594-846a-6980149b7d1d · outbound
This paper cites Phase-space interference in extensive and nonextensive quantum heat engines.
Optimizing quantum sensing networks via genetic algorithms and deep learning Phase-space interference in extensive and nonextensive quantum heat engines
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T03:22:58.041142Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 61b10fca-ed41-4d62-adc4-06d00e360299 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
Optimizing quantum sensing networks via genetic algorithms and deep learning Adam: A Method for Stochastic Optimization
Reference 61
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T03:22:01.251393Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.