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Paper Citation Record · LEDGER

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning

As of 14 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2412.06938.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.06938 v1

Coverage vector

measured 54 of 54 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-11T19:27:05.798866Z

measured 54 of 54 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

54 of 54 outbound references displayed

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  • unresolved32
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Outbound references

Observation 0e8efee0-a415-4ebe-8d26-a6e76b68e7d6 · outbound

This paper cites Wehner, D.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Wehner, D

Reference 1

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Observation 7ee31850-ead6-45ef-a366-94e0464942c2 · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 2

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Observation 919e5b1d-b930-4093-8210-a04df306a80d · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 3

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Observation 22e18bf7-0c2f-4365-b0f7-2c634c8ee414 · outbound

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Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 4

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Observation 2c71556c-613f-4420-849f-414ca44e0120 · outbound

This paper cites Universal blind quantum computation.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Universal blind quantum computation

Reference 5

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Observation 33c37da6-5b29-460e-9fe0-92336b2354b2 · outbound

This paper cites Gottesman, T.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Gottesman, T

Reference 6

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Observation 19894c32-c911-496c-993a-6c8ef1c9c5c2 · outbound

This paper cites Kómár, E.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Kómár, E

Reference 7

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Observation 4838e1f4-edef-437e-8e29-16a5c4140fa0 · outbound

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Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 8

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Observation a6bf0e9f-5d27-4728-bac4-b517ab66a094 · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 9

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source=pdf_text observed=2026-08-11T19:27:05.582737Z digest=sha256:17c2473e4789f9c6c4ec1b5afab96baf3d541a85a967f5c8d145b8b59dbff460

Observation 8fffd2fb-4d53-4353-9494-584ddd2f0acb · outbound

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Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 10

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Observation 6af1f385-4dc6-4ba8-9eb5-42eb3b54479c · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 11

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Observation f841f736-1b49-46b7-9171-17702a17381a · outbound

This paper cites Azuma, S.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Azuma, S

Reference 12

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Observation 983d4d23-35a6-40e2-b2a3-8537a04d6d01 · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 13

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Observation 08329922-45a1-4cf6-8d8b-d330d87a31e7 · outbound

This paper cites Event-ready-detectors.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Event-ready-detectors

Reference 14

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source=pdf_text observed=2026-08-11T19:27:05.606450Z digest=sha256:54a60f468b790103264d0d174737364fc809cf4f739fe82f3378d01f373559a7

Observation faac0975-d626-4dbe-b715-a8747e181d0e · outbound

This paper cites On noise in swap ASAP repeater chains: exact analytics, distributions and tight approximations.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning On noise in swap ASAP repeater chains: exact analytics, distributions and tight approximations

Reference 15

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Observation edaaa206-a130-4c8e-9e0a-d671bab24d94 · outbound

This paper cites Coopmans, S.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Coopmans, S

Reference 16

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Observation 32560899-03f5-41ba-bcbc-6d1876e8f4ab · outbound

This paper cites Kamin, E.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Kamin, E

Reference 17

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Observation 1f1da076-9edc-42af-99b8-4ce02aa6f17c · outbound

This paper cites Entanglement Swapping for Repeater Chains with Finite Memory Sizes.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Entanglement Swapping for Repeater Chains with Finite Memory Sizes

Reference 18

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Observation 9cfdb57f-00da-4a0c-a0cf-1d81c2d7448d · outbound

This paper cites On the Analysis of Quantum Repeater Chains with Sequential Swaps.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning On the Analysis of Quantum Repeater Chains with Sequential Swaps

Reference 19

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Observation bc654e91-a896-4a8a-851f-2f00d0f3057d · outbound

This paper cites Shchukin and P.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Shchukin and P

Reference 20

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Observation 2055aff2-66c3-46a6-8000-214d43dee948 · outbound

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Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 21

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Observation b41601d1-c5eb-4552-8908-89399aeaa717 · outbound

This paper cites Haldar, P.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Haldar, P

Reference 22

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Observation ea08e650-15d6-4063-a821-dad3a5c6279a · outbound

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Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 23

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Observation 370b9505-deff-49c2-bac3-c06919336662 · outbound

This paper cites Design and demonstration of an operating system for executing applications on quantum network nodes.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Design and demonstration of an operating system for executing applications on quantum network nodes

Reference 24

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Observation fe2066ee-e48f-4120-8232-581fea5fd2df · outbound

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Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

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Observation eec5bcf4-9e00-4a09-b431-6485e2e46804 · outbound

This paper cites Rozpędek, K.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Rozpędek, K

Reference 26

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Observation 0097bea0-0e73-425b-894e-5785a76469a6 · outbound

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Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 27

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Observation 395e895c-0b6e-42c3-b1af-937ca9480215 · outbound

This paper cites Reducing classical communication costs in multiplexed quantum repeaters using hardware-aware quasi-local policies.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Reducing classical communication costs in multiplexed quantum repeaters using hardware-aware quasi-local policies

Reference 28

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Observation af294ff2-3118-4d5e-98bb-5ab355adcf81 · outbound

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Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 29

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source=pdf_text observed=2026-08-11T19:27:05.676499Z digest=sha256:6999952644c79ecb95c11437ac659c0db783b7d4931222faaeef23ae04e2c7de

Observation a9182efe-061d-466c-bb53-852f848a2959 · outbound

This paper cites Deterministic delivery of remote entanglement on a quantum network.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Deterministic delivery of remote entanglement on a quantum network

Reference 30

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source=pdf_text observed=2026-08-11T19:27:05.681118Z digest=sha256:3120701b7216eb0536b2645883f0f94f9afb0fc06a96643aadbc52124673a2a7

Observation 31339a53-0f06-46ba-b53d-bc326c92dcc2 · outbound

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Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 31

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Observation 83e2ea50-ab16-49f8-a7aa-812e5f0bf295 · outbound

This paper cites Khatri, On the design and analysis of near-term quan- tum network protocols using Markov decision processes, AVS Quantum Science4, 030501 (2022).

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Khatri, On the design and analysis of near-term quan- tum network protocols using Markov decision processes, AVS Quantum Science4, 030501 (2022)

Reference 32

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Observation b0720a9f-9e60-4992-b717-de7200a31e66 · outbound

This paper cites Shchukin, F.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Shchukin, F

Reference 33

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Observation b05f6202-0fb2-426a-a269-5a55680bd84a · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 34

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Observation dafda167-5c79-4f27-a275-896d2c994869 · outbound

This paper cites Fast and reliable entanglement distribution with quantum repeaters: principles for improving protocols using reinforcement learning.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Fast and reliable entanglement distribution with quantum repeaters: principles for improving protocols using reinforcement learning

Reference 35

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Observation e8da3414-440c-4df3-b02b-1cdcd296b7c1 · outbound

This paper cites Coopmans,Tools for the Design of Quantum Repeater Networks, Ph.D.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Coopmans,Tools for the Design of Quantum Repeater Networks, Ph.D

Reference 36

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source=pdf_text observed=2026-08-11T19:27:05.710598Z digest=sha256:60f7e952f8a5e9c12d3ceabef02b5467f9ebe4074dfa225766bd3f544b78fcbd

Observation e9f6b940-b5cc-48d4-a900-d81f9839cf3a · outbound

This paper cites Raffin, A.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Raffin, A

Reference 37

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source=pdf_text observed=2026-08-11T19:27:05.715490Z digest=sha256:e30e98abc609f4c6d4d70aab37f266361acb3ed557737003c529acaa99533c7f

Observation 7ca5914e-d9b1-4824-87e8-0f3618f8538a · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 38

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unresolved
raw_fallback, observed 2026-08-11T19:27:06.362007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.720224Z digest=sha256:32353eaa69f97e12884a044c389713a5c56e1880a69fcebd7350a1459c621aee

Observation 6d472b6d-696d-4f2b-a6d8-5fb768e73ff7 · outbound

This paper cites The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T19:27:05.725101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:27:05.725101Z digest=sha256:457040cedebbb39a6f50e583e213de6f62310b8aa0bf72d3d21e6fc7bbbc8ac7

Observation 72f7a569-1b5a-415b-ba27-6f86aa677efd · outbound

This paper cites Zhu and X.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Zhu and X

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:27:06.345857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.730142Z digest=sha256:b53b8a329bb43b777095374d38963a5fc58444484572732d4eeda828ae4e4109

Observation 1c35b7be-de54-4542-965d-3f2abf76d8c8 · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-11T19:27:05.735043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:27:05.735043Z digest=sha256:b89626e89f59f911897f02b9cd0a99960cc04c0026382679b9201fd120fd01fe

Observation 6949d95d-f2ee-49b2-a8dc-0335436384d1 · outbound

This paper cites Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T19:27:05.739836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:27:05.739836Z digest=sha256:fe9a0b18f8246b5695280090f4cc859c813f4e73233e283dc4ee1d1843437136

Observation 31381f03-6aa6-405c-be7a-ab004c55327b · outbound

This paper cites Nägele and F.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Nägele and F

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:27:06.329759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.744740Z digest=sha256:507aa31fdab11e2c116c6d48f98f201f9521b0bc85a17b94c943b3f7227528a3

Observation e6fd5bfb-048c-4a7d-bfca-353e5f860d53 · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:27:06.314361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.749564Z digest=sha256:e05ab148ab596e6c7803a9b9338b2584cdcb62267515fbad440192d08d2a5d97

Observation 66f2117f-dcf8-4c2e-ab27-c2c91c4faf08 · outbound

This paper cites Buşoniu, R.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Buşoniu, R

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:27:06.298403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.754742Z digest=sha256:d779298fd366673092a446eaefb688bb30e03fa1d2d88c2c64ec8db3918b4623

Observation 628cf244-8513-4432-9059-0dd5cb631c04 · outbound

This paper cites Zhang, Z.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Zhang, Z

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:27:06.282639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.760192Z digest=sha256:f48ea6d4621dd6dcf66dc0fdd9c4ef69449ec81313488d943eb9881036a35be9

Observation 1d167c58-8946-495d-806b-267325a99b11 · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-11T19:27:05.765232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:27:05.765232Z digest=sha256:2cc13c18e95a8faf7d3ac83bf14612431357754c66525a35ce0efd3a17eb3817

Observation e5294a49-f066-4e36-9dfc-091129829898 · outbound

This paper cites Shahbeigi, D.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Shahbeigi, D

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:27:06.267850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.770326Z digest=sha256:f285dfeee04b6db510db9bbbe9e09c2e02acbbc872c9655386d6cc9cdc7a51c5

Observation cd70b097-4e47-45de-93df-a376be3c8efe · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:27:06.251126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.775783Z digest=sha256:4ce733e1b2ed16186233b0ad936fb4af8841f922f066935a5894261cdf0def08

Observation dc48dfac-eaaf-4143-b8e7-0ed9d46bae0a · outbound

This paper cites Here n ∈ N is the number of nodes in the linear network, where each node is labelled by an integer i ∈ [n].

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Here n ∈ N is the number of nodes in the linear network, where each node is labelled by an integer i ∈ [n]

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:27:06.232811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.780296Z digest=sha256:d92770b6488637582746b2fc7da4e49aef2c5ef0401b8d596edec0dcb4d6c8e3

Observation d02fe90b-ddd0-40d1-bac2-8c83758ab54e · outbound

This paper cites When the link gen- eration attempt is applied, it first removes all links con- nected to qubits at segmenti, i.e.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning When the link gen- eration attempt is applied, it first removes all links con- nected to qubits at segmenti, i.e

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:27:06.216844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.784841Z digest=sha256:d838bb3e226bc7507fbe43d13e38de68fb9f250d6d286a3d66bac3d715c0e66b

Observation 5f98ef5a-f381-41ed-9dfd-929e3a7aaf1d · outbound

This paper cites In each even round, it will perform a swap on all of the nodes where two links are present.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning In each even round, it will perform a swap on all of the nodes where two links are present

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:27:06.201280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.789912Z digest=sha256:b4de03416cca844d0cab67e11a382489f64885491dc2893b10c6f67e5a9cb5b5

Observation 2c5c80d1-b6a7-43df-b409-366d976b790b · outbound

This paper cites This is to ensure that each time after sending out actions, enough time has passed such that all results have been collected back.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning This is to ensure that each time after sending out actions, enough time has passed such that all results have been collected back

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:27:06.185432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.794036Z digest=sha256:718591ced83cb0e6ef3056b083cafba33b5e9b9cf35315e1829e5f5a382208df

Observation 9d04a2d5-efe0-4174-9236-add6aa99107f · outbound

This paper cites an unresolved cited work.

Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:27:06.168889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:27:05.798866Z digest=sha256:a6219638a6a6f95b7693438dc650fba9849776fb344ee3057b39b0bf8e9a50a6

Pith citing papers

No inbound Pith citation observations are available.