During the first reporting period, we developed a full‑stack simulation and analysis workflow to validate fault‑tolerant architectures across the project’s hardware platforms. It links device‑level parameters to logical error rates by combining physical modeling, logical simulation, and architectural constraints.
We have produced five interoperable libraries to model hardware‑specific imperfections. For linear‑optical systems, a tensor‑network simulator for photonic resource‑state generation models photon loss, beam‑splitter imbalance, and phase errors and is used to compute fusion‑network success probabilities and resource‑state fidelity. For matter‑based platforms (trapped ions and spin qubits), a physics‑aware simulator solves time‑dependent Lindblad master equations and outputs Pauli transfer matrices and Kraus operators, converting Hamiltonian controls into discrete error channels for fault‑tolerance analysis.
In the quantum‑ldpc‑sim package, we have consolidated support for LDPC code families such as Bivariate Bicycle, Twisted Torus, and Lifted Product. We have also implemented circuit constructions and logical operations using transversal‑gate methods. The logical‑gates‑sim package generates fault‑tolerant Hadamard and CNOT circuits for planar, rotated, and subsystem surface codes and exports them to standard simulators. Using noise models from the physical simulators, the generated logical circuits were run to produce threshold plots. The results show logical error suppression below physical error rates and provide quantitative benchmarks for the transversal‑gate designs.
We have also implemented a GPU state‑vector simulator in the gpu‑qubit‑sim package. This library supports higher‑dimensional qudits (d≥2) and accelerates simulations relative to CPU baselines, enabling high‑dimensional encoding studies.
We have studied photonic imperfections and found photon loss and mode mismatch to be the dominant imperfections. Analysis shows conventional approaches require <1% loss, while exposure‑based adaptive schemes tolerate up to 18.8% Loss Per Photon Threshold (LPPT), with intermediate thresholds in the 6–10% range. Engineering targets set for quantum‑dot and LNoI platforms: <10% per‑photon loss (conservative) or <6% (aggressive), together with >96% photon indistinguishability (corresponding to the 4% distinguishability threshold). These targets will be used as acceptance criteria for the architectural blueprints.
For optically addressable spin‑1 systems, we mapped platform‑specific non‑idealities (off‑resonant crosstalk, optical‑dipole interactions during readout, and lattice defects) to logical error models. The analysis quantified the density–addressability trade‑off and defined mitigation requirements for surface‑code‑compatible performance.
