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quant-ph2026

Multi-agent Autoformalization of Tensor Network Theory

Sirui Lu, Erickson Tjoa, J. Ignacio Cirac

We build a team of specialized large language-model agents and present an agent-driven workflow for research-level formalization in theoretical physics, with the autoformalization…

quant-ph2026

Benchmark of quantum algorithms for ground state preparation in the presence of noise

Daniel Molpeceres, Sirui Lu, J. Ignacio Cirac +1

We compare the performance of representative cooling, adiabatic, and optimization algorithms for ground-state preparation in the presence of noise. Using an exactly solvable family…

quant-ph2026

Co-Designing Quantum Codes with Transversal Diagonal Gates via Multi-Agent Systems

Xi He, Sirui Lu, Bei Zeng

Exact scientific discovery requires more than heuristic search: candidate constructions must be turned into exact objects and checked independently. We address this gap by extendin…

quant-ph2025

Quantum algorithms for cooling: a simple case study

Daniel Molpeceres, Sirui Lu, J. Ignacio Cirac +1

Preparation of low-energy quantum many-body states has a wide range of applications in quantum information processing and condensed matter physics. Quantum cooling algorithms offer…

quant-ph2025

Variational Neural and Tensor Network Approximations of Thermal States

Sirui Lu, Giacomo Giudice, J. Ignacio Cirac

We introduce a variational Monte Carlo algorithm for approximating finite-temperature quantum many-body systems, based on the minimization of a modified free energy. This approach…