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Institute for Advanced Study

Academic institutionnorthamerica · us
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Research library66linked papers
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Selected work

Representative Papers

Non-Abelian qLDPC: TQFT Formalism, Addressable Gauging Measurement and Application to Magic State Fountain on 2D Product Codes

Jan 11, 2026

This work addresses the challenge of reconciling connectivity and universality in two-dimensional architectures for fault-tolerant quantum computation with qLDPC codes. By generalizing Kitaev’s non-Abelian topological code to non-Abelian qLDPC codes, the authors construct a combinatorial topological quantum field theory based on Poincaré CW complexes and introduce a spacetime path integral formulation to enable addressable gauge measurements. The key innovation lies in the first realization of native non-Clifford logical gates on constant-rate two-dimensional hypergraph product codes, achieved through an addressable measurement scheme rooted in 0-form subcomplex symmetries, which is further extended to higher-dimensional and higher-order symmetries. This approach is successfully applied to magic state distillation, enabling the parallel preparation of $O(\sqrt{n})$ disjoint CZ magic states, each with code distance $O(\sqrt{n})$, on $n$ physical qubits.

4 citations2 influentialRead paper

QAC0 Contains TC0 (with Many Copies of the Input)

Jan 06, 2026arXiv.org

This work investigates the computational power of constant-depth quantum circuits, denoted $\mathsf{QAC}^0$, and their advantage over classical constant-depth circuits $\mathsf{AC}^0$. By introducing multiple copies of the input and leveraging amplitude amplification, the authors transform approximate quantum constructions into exact implementations. This approach yields the first unconditional separation $\mathsf{QAC}^0 \not\subseteq \mathsf{AC}^0[p]$ for any prime $p$, and establishes the inclusion $\mathsf{TC}^0 \subseteq \mathsf{QAC}^0 \circ \mathsf{NC}^0$. The results not only clarify the superiority of $\mathsf{QAC}^0$ in computing nontrivial Boolean functions but also provide novel techniques for designing constant-depth quantum circuits.

2 citations1 influentialRead paper
Recent publications

Latest Papers

Unknown Unknowns: Model Misspecification in Machine Learning for Physics

Aug 13, 2026

This study addresses the risks of unknown unknowns arising from model misspecification in physical inverse problems by proposing an iterative diagnosis and mitigation framework. Treating misspecification as an opportunity for discovery, this work establishes a closed-loop detection-mitigation analytical paradigm that integrates complementary diagnostics, iterative updating, and robustness analysis strategies. Consequently, this research develops a systematic methodology for managing unknown unknowns, effectively enhancing model robustness against unforeseen biases and significantly improving the reliability of physical measurements. Ultimately, the proposed framework provides a novel safety assurance mechanism for solving complex inverse problems, ensuring greater confidence in computational reconstructions where model fidelity cannot be fully guaranteed a priori.

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