arXiv subjects

Shuangshuang Fu

Publications and source records attributed to Shuangshuang Fu.

5 recordsLinked to original sources

arXiv2026

Complexity of quantum states in the stabilizer formalism

We initiate an investigation into a notion of state complexity for discrete-variable quantum systems. Specifically, we propose an information-theoretic quantifier for the complexity of quantum states within the stabilizer formalism of quantum computation. This is achieved by leveraging the symmetric Jordan product (associated with classicality) and the skew-symmetric Lie product (linked to quantumness) between the square root of the quantum state and the Heisenberg-Weyl displacement operators. We establish the fundamental properties of this quantifier and demonstrate that state complexity is closely related to the nonstabilizerness of quantum states via the $L^4$-norm of their characteristic functions.

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arXiv2015

Forgetting in the Synchronization of Quantum Networks

In this paper, we study the decoherence property of synchronization master equation for networks of qubits interconnected by swapping operators. The network Hamiltonian is assumed to be diagonal with different entries so that it might not be commutative with the swapping operators. We prove a theorem establishing a general condition under which almost complete decohernece is achieved, i.e., all but two of the off-diagonal entries of the network density operator asymptotically tend to zero. This result explicitly shows that quantum dissipation networks tend to forget the information initially encoded when the internal (induced by network Hamiltonian) and external (induced by swapping operators) qubit interactions do not comply with each other.

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arXiv2015

Reaching Quantum Consensus with Directed Links: Missing Symmetry and Switching Interactions

In this paper, we study consensus seeking of quantum networks under directed interactions defined by a set of permutation operators among a network of qubits. The state evolution of the quantum network is described by a continuous-time master equation, for which we establish an unconditional convergence result indicating that the network state always converges with the limit determined by the generating subgroup of the permutations making use of the Perron-Frobenius theory. We also give a tight graphical criterion regarding when such limit admits a reduced-state consensus. Further, we provide a clear description to the missing symmetry in the reduced-state consensus from a graphical point of view, where the information-flow hierarchy in quantum permutation operators is characterized by different layers of information-induced graphs. Finally, we investigate quantum synchronization in the presence of network Hamiltonian, study quantum consensus conditions under switching interactions, and present a few numerical examples illustrating the obtained results.

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arXiv2015

The Evolution of Network Entropy in Classical and Quantum Consensus Dynamics

In this paper, we investigate the evolution of the network entropy for consensus dynamics in classical or quantum networks. We show that in the classical case, the network entropy decreases at the consensus limit if the node initial values are i.i.d. Bernoulli random variables, and the network differential entropy is monotonically non-increasing if the node initial values are i.i.d. Gaussian. While for quantum consensus dynamics, the network's von Neumann entropy is in contrast non-decreasing. In light of this inconsistency, we compare several gossiping algorithms with random or deterministic coefficients for classical or quantum networks, and show that quantum gossiping algorithms with deterministic coefficients are physically related to classical gossiping algorithms with random coefficients.

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arXiv2014

Feedback Policies for Measurement-based Quantum State Manipulation

In this paper, we propose feedback designs for manipulating a quantum state to a target state by performing sequential measurements. In light of Belavkin's quantum feedback control theory, for a given set of (projective or non-projective) measurements and a given time horizon, we show that finding the measurement selection policy that maximizes the probability of successful state manipulation is an optimal control problem for a controlled Markovian process. The optimal policy is Markovian and can be solved by dynamical programming. Numerical examples indicate that making use of feedback information significantly improves the success probability compared to classical scheme without taking feedback. We also consider other objective functionals including maximizing the expected fidelity to the target state as well as minimizing the expected arrival time. The connections and differences among these objectives are also discussed.

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