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Steven Baldasty

Publications and source records attributed to Steven Baldasty.

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Qoreo: Choreographic Programming for Quantum Distributed Systems

Programming distributed quantum systems requires multiple actors to coordinate precise sequences of quantum operations, classical communication, and entanglement generation. Writing such protocols directly as distributed processes is tedious and error-prone, and subtle mismatches can cause deadlock or silently incorrect quantum states. We present Qoreo, a choreographic programming language for quantum distributed systems in which an entire protocol is expressed as single, global program (a choreography) rather than as a collection of independent actor processes. Qoreo includes a local quantum language with linear types that enforce the no-cloning principle; a choreographic language that combines local quantum computation with inter-actor classical and quantum communication; and a process language for individual network nodes. We prove type safety for choreographies, guaranteeing that well-typed programs implement well-defined quantum operations, and we define endpoint projection~(EPP), which automatically derives a network of independent processes from any choreography. We prove EPP sound and complete with respect to the choreographic semantics; as a corollary, every well-typed choreography projects to a deadlock-free process network. The metatheory of Qoreo is fully mechanized in Rocq, and we provide an extraction pipeline to NetQASM for simulation and deployment on quantum network hardware.

quant-ph

Probabilistic, Resource-Aware, Asynchronous, Out-of-Order Choreographies

Futures-based implementations of out-of-order choreographies can substantially improve latency and throughput, but their actual behavior depends on resources such as communication delay, computation time, failures, and recovery. Existing formal models such as Ozone's O3 describe which executions are possible, but do not directly explain how likely those executions are or how long they take. In this work we present AsInst, a probabilistic, resource-aware language for modeling the semantics of asynchronous choreographies with out-of-order execution. AsInst programs are interpreted as temporal Bayesian networks that model both the values produced at runtime and the times at which they become available. We prove that this central semantics correctly captures a corresponding futures-style network semantics. We also show that AsInst can encode Ozone-style select-and-merge conditionals, and we use case studies to model communication-failure recovery and analyze runtime performance.

cs.PL

SoK: Usability Studies in Differential Privacy

Differential Privacy (DP) has emerged as a pivotal approach for safeguarding individual privacy in data analysis, yet its practical adoption is often hindered by challenges in the implementation and communication of DP. This paper presents a comprehensive systematization of existing research studies around the usability of DP, synthesizing insights from studies on both the practical use of DP tools and strategies for conveying DP parameters that determine privacy protection levels, such as epsilon($\varepsilon$). By reviewing and analyzing these studies, we identify core usability challenges, best practices, and critical gaps in current DP tools that affect adoption across diverse user groups, including developers, data analysts, and non-technical stakeholders. Our analysis highlights actionable insights and pathways for future research that emphasizes user-centered design and clear communication, fostering the development of more accessible DP tools that meet practical needs and support broader adoption.

cs.HC