TL;DR
This work presents a machine-learning-based protocol to quantify the purity of an arbitrary two-qubit Werner state without requiring knowledge of its underlying ideal form using only nine measurement bases.
Estimating the quantum Fisher information (QFI) is a central task in quantum science and technology, underpinning the benchmarking of measurement devices and the certification of metrological advantages. Owing to the highly nonlinear dependence of the QFI on the quantum state, achieving efficient estimates that reliabl...
A Transformer-based Quantum State Characterizer model is proposed for noisy RSP experiments that enables accurate tomographic characterization under dynamic noise and provides physically grounded post-hoc insights, holding promise for intelligent quantum information processing applications.
Entangled photons play a crucial role in quantum applications, and determining and characterising their entanglement is vital to using them effectively. High-dimensional entangled states offer richer possibilities, but their additional measurement degrees of freedom make them increasingly demanding to characterise. How...
A novel QST protocol that utilizes Kirkwood-Dirac (KD) quasiprobability to reconstruct quantum states, which enables state reconstruction with only two complementary rank-one projective measurements, thus significantly reducing the measurement cost.
Entanglement witnesses are essential for certifying entanglement, yet constructing ones that are both noise-robust and economical in measurement settings remains challenging - particularly beyond qubits and for non-stabilizer ("magic") states. We present a machine-learning method that, given a target state and a user-s...
FlowMeas is introduced, which uses a generative flow network to directly sample finite ensembles of shallow Clifford measurement circuits subject to a prescribed shot budget and hardware constraints, and establishes generative learning as a flexible and unified framework for quantum measurement design under practical r...
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