2024/03/15 by Paula Belzig, Belzig, Paula
Computer Science · Physics and Astronomy · #Chaos control and synchronization #Chaos-based Image/Signal Encryption #FOS: Physical sciences #Neural Networks and Applications #Quantum Physics (quant-ph)
paper · pdf · doi:10.48550/arxiv.2403.10592
openalex publication_date 2024/03/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Symmetries are of fundamental interest in many areas of science. In quantum information theory, if a quantum state is invariant under permutations of its subsystems, it is a well-known and widely used result that its marginal can be approximated by a mixture of tensor powers of a state on a single subsystem. Applications of this quantum de Finetti theorem range from quantum key distribution (QKD) to quantum state tomography and numerical separability tests. Recently, it has been discovered by Gross, Nezami and Walter that a similar observation can be made for a larger symmetry group than permutations: states that are invariant under stochastic orthogonal symmetry are approximated by tensor powers of stabilizer states, with an exponentially smaller overhead than previously possible. This naturally raises the question if similar improvements could be found for applications where this symmetry appears (or can be enforced). Here, two such examples are investigated.