@informaq.bsky.socialNew protocols for efficient tomography of bosonic quantum states achieve optimal Gaussian approximations in both high and low fidelity regimes, with the first tolerant Gaussianity testing method and proof that non-Gaussian measurements are necessary.
@informaq.bsky.socialDeveloped efficient algorithms to learn sparse quantum states using only single-qubit measurements with polynomial sample complexity, enabling practical state tomography of entangled systems on current NISQ devices without entangling gates.
@informaq.bsky.socialNew tomography method enables polynomial-sample reconstruction of mixed quantum states with extensive entanglement and magic by exploiting hidden block structure, surpassing prior methods limited to restricted state classes.
@informaq.bsky.socialQuantum network tomography requires probe path constraints beyond measurement completeness. Novel FIM analysis reveals that topology and monitor placement critically determine link parameter identifiability.
@informaq.bsky.socialNovel algorithms achieve near-optimal complexity for learning k-sparse quantum states: Õ(k/ε) samples and Õ(kn/ε) time for pure states, with extension to mixed states via purification.
@informaq.bsky.socialPhysicists develop a quantum tomography technique proving entanglement in mixed-spin hadrons can be certified from incomplete experimental data, enabling direct studies of how quantum spin correlations evolve during QCD hadronization.
@informaq.bsky.socialResearchers proved optimal sample complexity for learning low-rank quantum states, demonstrating that jointly measuring t samples improves over single-sample tomography by factor √t, with matching algorithmic and information-theoretic bounds.
@informaq.bsky.socialResolves open question in quantum state tomography by proving tight lower bounds for protocols where each measurement acts on k copies, removing earlier restrictions and determining optimal copy complexity.