An efficient Bures-distance algorithm for fermionic Gaussian states shows linear average subsystem-distance growth in the integrable Ising chain, but not in quadratic SYK or random Gaussian states.
Subsystem Trace-Distances of Two Random States
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abstract
We study two-state discrimination in chaotic quantum systems. Assuming that one of two $N$-qubit pure states has been randomly selected, the probability to correctly identify the selected state from an optimally chosen experiment involving a subset of $N-N_B$ qubits is given by the trace-distance of the states, with $N_B$ qubits partially traced out. In the thermodynamic limit $N\to\infty$, the average subsystem trace-distance for random pure states makes a sharp, first order transition from unity to zero at $f=1/2$, as the fraction $f=N_B/N$ of unmeasured qubits is increased. We analytically calculate the corresponding crossover for finite numbers $N$ of qubits, study how it is affected by the presence of local conservation laws, and test our predictions against exact diagonalization of models for many-body chaos.
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Efficient computation of average subsystem Bures distance between fermionic Gaussian states
An efficient Bures-distance algorithm for fermionic Gaussian states shows linear average subsystem-distance growth in the integrable Ising chain, but not in quadratic SYK or random Gaussian states.