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We study the problem of minimizing round complexity in the context of succinct classical argument systems for quantum computation. We design a 4-round public-coin argument system for batchQMA languages and a 6-round private-coin argument system for monotone policy batchQMA languages, both under post-quantum hardness assumptions. Unlike all previous works, we do not rely on state-preserving succinct arguments of knowledge for NP. Our main technical contribution is a new approach to prove soundness without rewinding cheating provers, using straight-line partial extractability.

We present Cloudscape, a dataset of nearly 400 cloud architectures deployed on AWS. We perform an in-depth analysis of the usage of storage services in cloud systems. Our findings include: S3 is the most prevalent storage service (68%), while file system services are rare (4%); heterogeneity is common in the storage layer; storage services primarily interface with Lambda and EC2, while also serving as the foundation for more specialized ML and analytics services. Our findings provide a concrete understanding of how storage services are deployed in real-world cloud architectures, and our analysis of the popularity of different services grounds existing research.

LambdaStore is a data-centric serverless platform that breaks the split between stateless functions and external storage in classic cloud computing platforms. By scheduling serverless invocations near data instead of pulling data to compute, LambdaStore substantially reduces the state access cost that dominates today's serverless workloads. Leveraging its transactional storage engine, LambdaStore delivers serializable guarantees and exactly-once semantics across chains of lambda invocations. Under read-heavy workloads, LambdaStore lifts throughput by orders of magnitude over existing serverless platforms while holding end-to-end latency below 20 ms.