Aliki A. Capatos | Searcharxiv

arXiv2026

Purification of photonic graph states

Graph states constitute the main building block for quantum computing with photons. Quantum emitters with a hosted spin can deterministically generate photonic graph states, strongly lowering the overhead of multiplexing highly probabilistic linear-optics graph state generation. However, they generally suffer from various noise sources, resulting in reduced fidelities of the produced states. To mitigate this issue, we develop purification schemes for entangled photonic states. We first develop purification schemes to purify arbitrary photonic GHZ and other CSS states, which we generalize to all photonic graph states and stabilizer states. The proposed purification schemes have a high success probability of up to $1/2$ and require only linear optics and photon detectors. We optimize cascaded purification schemes for various graph states, taking into account phenomenological Pauli errors or physical noise in time-bin-encoded graph state generation with quantum emitters.

quant-ph↗

arXiv2026

The dynamic 4.8.8 Floquet code

Fault-tolerant quantum memories depend on the syndrome extraction circuit as much as on the underlying code. Ancilla-free or dynamic circuits are an effective way to improve this circuit layer. For the 6.6.6 honeycomb Floquet code, making the circuit dynamic raises the threshold and lowers the qubit overhead, but at the cost of halving the spatial code distance. A dynamic construction for the 4.8.8 lattice layout was conjectured to preserve full distance. I confirm this and give a dynamic measurement circuit for the CSS 4.8.8 Floquet code. To benchmark it, I construct and compare four circuit-level implementations on a torus, including two dynamic variants (with and without mid-circuit resets), the standard ancilla-based circuit, and a pipelined ancilla-based circuit. Under circuit-level depolarising noise, the reset dynamic circuit reaches a per-round threshold of $0.463\%$ $(0.490\%)$ with MWPM (BP+matching), while the no-reset variant reaches the highest threshold of all four circuits at $0.512\%$ $(0.574\%)$. The standard ancilla-based circuit only achieves $0.228\%$ $(0.240\%)$, but the pipelined schedule reaches $0.478\%$ $(0.489\%)$. The reset dynamic circuit also has a faster-growing timelike distance, with $2\le d_t/n_{\mathrm{qec}}\le 3$ asymptotically against a tight $3/2$ for the other three, and running it for fewer rounds gives the smallest spacetime volume in the fast-reset regime, while the no-reset variant is smallest in the slow-reset regime. The 4.8.8 dynamic circuits therefore see the expected threshold gain and overhead reduction without the spatial-distance cost, demonstrating the advantage of dynamic syndrome extraction in Floquet codes.

quant-ph↗