Publications

2026

1. arXiv

   Optimizing Parallel Execution of Commuting Pauli Product Rotations

   Sayam Sethi, Devika Nambisan, and Jonathan Mark Baker

   2026
2. QCE

   Price and Payoff: Non-Determinism in Fault Tolerant Quantum Computation

   Aditi Awasthi, Sayam Sethi, Sahil Khan, and 2 more authors

   2026
3. QCE

   INJEQT: Improved Magic-State Injection Protocol for Fault-Tolerant Quantum Extractor Architectures

   Sayam Sethi, Sahil Khan, Aditi Awasthi, and 2 more authors

   2026
4. arXiv

   Architecting Early Fault Tolerant Neutral Atoms Systems with Quantum Advantage

   Sahil Khan, Sayam Sethi, Kaavya Sahay, and 6 more authors

   2026
5. arXiv

   Logical Compilation for Multi-Qubit Iceberg Patches

   Cordell Mazzetti, Sayam Sethi, Rich Rines, and 2 more authors

   2026
6. arXiv

   Optimizing Logical Mappings for Quantum Low-Density Parity Check Codes

   Sayam Sethi, Sahil Khan, Maxwell Poster, and 2 more authors

   2026

2025

1. ASPLOS

   RESCQ: Realtime Scheduling for Continuous Angle Quantum Error Correction Architectures

   Sayam Sethi, and Jonathan Mark Baker

   In Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2, Rotterdam, Netherlands, 2025

   Abs DOI Code Slides

   In order to realize large scale quantum error correction (QEC), resource states, such as |T〉, must be prepared which is expensive in both space and time. In order to circumvent this problem, alternatives have been proposed, such as the production of continuous angle rotation states [1, 6, 34]. However, the production of these states is non-deterministic and may require multiple repetitions to succeed. The original proposals suggest architectures which do not account for realtime (or dynamic) management of resources to minimize total execution time. Without a realtime scheduler, a statically generated schedule will be unnecessarily expensive. We propose RESCQ (pronounced rescue), a realtime scheduler for programs compiled onto these continuous angle systems. Our scheme actively minimizes total cycle count by on-demand redistribution of resources based on expected production rates. Depending on the underlying hardware, this can cause excessive classical control overhead. We further address this by dynamically selecting the frequency of our recomputation. RESCQ improves over baseline proposals by an average of 2x in cycle count.

2024

1. QCE

   CQM: Cyclic Qubit Mappings

   Maxwell Poster, Sayam Sethi, and Jonathan M. Baker

   In 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), Sep 2024

   Abs DOI

   Quantum computers show promise to solve select problems otherwise intractable on classical computers. How-ever, noisy intermediate-scale quantum (NISQ) era devices are currently prone to various sources of error. Quantum error correction (QEC) shows promise as a path towards fault tolerant quantum computing. Surface codes, in particular, have become ubiquitous throughout literature for their efficacy as a quantum error correcting code, and can execute quantum circuits via lattice surgery operations. Lattice surgery also allows for logical qubits to maneuver around the architecture, if there is space for it. Hardware used for near-term demonstrations have both spatially and temporally varying error results in logical qubits. By maneuvering logical qubits around the topology, an average logical error rate (LER) can be enforced. We propose cyclic qubit mappings (CQM), a dynamic remapping technique implemented during compilation to mitigate hardware heterogeneity by expanding and contracting logical qubits. In addition to LER averaging, CQM shows initial promise given it’s minimal execution time overhead and effective resource utilization.

2. 3D-TemPo: Optimizing 3-D DRAM Performance Under Temperature and Power Constraints

   Shailja Pandey, Sayam Sethi, and Preeti Ranjan Panda

   IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Aug 2024

   Abs DOI

   3-D DRAM provides a significant performance boost resulting from substantial memory bandwidth. However, the stacked memory architecture exhibits high power density, causing thermal hotspots. Further, systems under power constraints require careful planning for intelligent allocation of the available power to their various components. A straightforward dynamic power management policy of allocating more power to potentially high memory activity 3-D DRAM ranks so as to maximize system performance causes a rise in the temperature of such ranks, making them susceptible to thermal stalls and shutdown by dynamic thermal management (DTM) strategies. A rise in rank temperature, in turn, increases the leakage power of memory ranks, affecting power budgeting decisions. Thus, a coordinated strategy for power budgeting and thermal management is needed. We propose an adjacency-aware dynamic power budgeting technique, 3D-TemPo, which dynamically performs a reward-based power allocation to memory ranks, in order to maximize 3-D DRAM performance under power and thermal constraints, and is sensitive to strong thermal correlations between vertically adjacent ranks. We evaluate 3D-TemPo using SPEC CPU2017 and PARSEC 2.1 benchmark suites and observe speedups of 1 times to 17.94 times compared to baseline strategies.