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Logical fermions for fault-tolerant quantum simulation
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abstract
We show how to absorb fermionic quantum simulation's expensive fermion-to-qubit mapping overhead into the overhead already incurred by surface-code-based fault-tolerant quantum computing. The key idea is to process information in surface-code twist defects, which behave like logical Majorana fermions. Our approach encodes Dirac fermions, a key data type for simulation applications, directly into logical Majorana fermions rather than atop a logical qubit layer in the architecture. Using quantum simulation of the $N$-fermion 2D Fermi-Hubbard model as an exemplar, we demonstrate two immediate algorithmic improvements. First, by preserving the model's locality at the logical level, we reduce the asymptotic Trotter-Suzuki quantum circuit depth from $\mathcal{O}(\sqrt{N})$ in a typical Jordan-Wigner encoding to $\mathcal{O}(1)$ in our encoding. Second, by exploiting optimizations manifest for logical fermions but less obvious for logical qubits, we reduce the $T$-count of the block-encoding \textsc{select} oracle by 20\% over standard implementations, even when realized by logical qubits and not logical fermions.
Forward citations
Cited by 2 Pith papers
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High-Distance Error-Correcting Codes for Fermion-to-Qubit Mappings in 2D and 3D
A new family of fermion-to-qubit stabilizer codes in 2D and 3D achieves arbitrarily large code distance with constant-weight stabilizers and local logical operators, with the 3D construction being the first of its kind.
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Graphical Calculus for Fermionic Tensors
A parity-aware graphical calculus extends the ZX diagram language to fermionic modes, covering Gaussian states, partial traces, purification, fermionization/bosonization, and fermionic error-correcting codes.
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