Memory-Optimal Sequential Synthesis of Multimode Gaussian Transformations
Abstract
In modular quantum computing architectures, communication between hardware modules is mediated by traveling qumodes sent through transmission lines. Each output qumode interacts with the emitting module only once through a beam-splitter-type interaction and becomes inaccessible to that module after emission. Information required for subsequent outputs must therefore remain in long-lived memory qumodes. For a prescribed multimode Gaussian transformation on N qumodes, this work determines the minimum memory cost for any given emission order, constructs an explicit sequential protocol attaining this minimum, and develops a greedy method for identifying memory-efficient emission orders. The transformation is represented by a symplectic matrix S, specified either directly or through a Gaussian gate sequence. The exact minimum memory cost is obtained from the ranks of submatrices of S and further reduces to a support-based counting rule whose computational cost is linear in the size of the support data. When S is specified directly, a matrix-based protocol attains the minimum memory cost. If instead S is specified through a gate sequence, the original gates can be reused without additional synthesis, although the resulting memory usage need not be minimal. Gaussian transformations with local support on a D-dimensional cubic lattice can be realized sequentially with O(N(D−1)/D) memory qumodes. The protocols also apply to non-Gaussian inputs, including GKP and cat states, and thereby provide an explicit, resource-efficient scheme for intermodule communication in modular architectures for universal continuous-variable quantum computation.
Related
- Near-optimal synthesis of non-Gaussian phase gates via qubit-oscillator Rabi control
- Reconfigurable Linear Optical Transformations in a Single Integrated Multimode Waveguide
- Reconstruction and Synthesis of Arbitrary Optical Intensity Patterns in Extremely Multimode Waveguide Cavities via Physics-Informed Optimized Modal Superposition
- Programmable high-dimensional state synthesis through a 20-m multimode fiber via long-coherence atomic photons
- Gaussian entanglement and quantum communication: geodesic optimization and multimode bounds
BibTeX
@misc{guo2026memoryoptimal,
title = {{Memory-Optimal Sequential Synthesis of Multimode Gaussian Transformations}},
author = {Fucheng Guo and Frank Mueller and Yuan Liu},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.05250},
eprint = {2609.05250},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.05250},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Memory-Optimal Sequential Synthesis of Multimode Gaussian Transformations
AU - Fucheng Guo
AU - Frank Mueller
AU - Yuan Liu
PY - 2026
DA - 2026/09/04
PB - arXiv
DO - 10.48550/arxiv.2609.05250
UR - https://arxiv.org/abs/2609.05250
AB - In modular quantum computing architectures, communication between hardware modules is mediated by traveling qumodes sent through transmission lines. Each output qumode interacts with the emitting module only once through a beam-splitter-type interaction and becomes inaccessible to that module after emission. Information required for subsequent outputs must therefore remain in long-lived memory qumodes. For a prescribed multimode Gaussian transformation on N qumodes, this work determines the minimum memory cost for any given emission order, constructs an explicit sequential protocol attaining this minimum, and develops a greedy method for identifying memory-efficient emission orders. The transformation is represented by a symplectic matrix S, specified either directly or through a Gaussian gate sequence. The exact minimum memory cost is obtained from the ranks of submatrices of S and further reduces to a support-based counting rule whose computational cost is linear in the size of the support data. When S is specified directly, a matrix-based protocol attains the minimum memory cost. If instead S is specified through a gate sequence, the original gates can be reused without additional synthesis, although the resulting memory usage need not be minimal. Gaussian transformations with local support on a D-dimensional cubic lattice can be realized sequentially with O(N^(D−1)/D) memory qumodes. The protocols also apply to non-Gaussian inputs, including GKP and cat states, and thereby provide an explicit, resource-efficient scheme for intermodule communication in modular architectures for universal continuous-variable quantum computation.
ER -