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Shared Randomness in Locally Checkable Problems: The Role of Computational Assumptions

Published: April 24, 2025 | arXiv ID: 2504.17583v2

By: Adar Hadad, Moni Naor

Potential Business Impact:

Makes computers solve hard problems faster with shared secrets.

Business Areas:
Collaborative Consumption Collaboration

Shared randomness is a valuable resource in distributed computing, allowing some form of coordination between processors without explicit communication. But what happens when the shared random string can affect the inputs to the system? Consider the class of distributed graph problems where the correctness of solutions can be checked locally, known as Locally Checkable Labelings (LCL). LCL problems have been extensively studied in the LOCAL model, where nodes operate in synchronous rounds and have access only to local information. This has led to intriguing insights regarding the power of private randomness. E.g., for certain round complexity classes, derandomization does not incur an overhead (asymptotically). This work considers a setting where the randomness is public. Recently, an LCL problem for which shared randomness can reduce the round complexity was discovered by Balliu et al. (ICALP 2025). This result applies to inputs set obliviously of the shared randomness, which may not always be a plausible assumption. We define a model where the inputs can be adversarially chosen, even based on the shared randomness, which we now call preset public coins. We study LCL problems in the preset public coins model, under assumptions regarding the computational power of the adversary that selects the input. We show connections to hardness in the class TFNP. Our results are: 1. Assuming a hard-on-average problem in TFNP, we present an LCL problem that, in the preset public coins model, demonstrates a gap in the round complexity between polynomial-time and unbounded adversaries. 2. An LCL problem for which the error probability is significantly higher when facing unbounded adversaries implies a hard-on-average problem in TFNP/poly.

Country of Origin
🇮🇱 Israel

Page Count
64 pages

Category
Computer Science:
Distributed, Parallel, and Cluster Computing