Protocol learns k-local Lindbladians to ε accuracy with Õ(n^{2k}/ε²) samples and projects to valid generators; improves to log n under sparsity assumptions.
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Society for Industrial and Applied Mathematics (1994)
6 Pith papers cite this work, alongside 2,749 external citations. Polarity classification is still indexing.
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A new single-SDP rounding method for Lovász theta that provably recovers maximum weighted stable sets in generalized split graphs and other perfect graph subclasses via value function approximation and dynamic programming.
Introduces forward-assisted purification via a new spatiotemporal framework that outperforms conventional static purification by up to 50x in copy efficiency and circumvents no-purification theorems for Bell states.
Denormalized Lorentzian Laurent series are defined and used to prove new bounds for integral flows on DAGs and weight-space dimensions in parabolic sl_{n+1} Verma modules.
SILAS jointly optimizes polynomial ODE vector fields and polynomial Lyapunov functions from data to produce models with provably bounded trajectories via compact absorbing sets.
An interior-point method is introduced to compute dynamical quantum optimal transport geodesics on density matrices, shown to approximate some quantum chemistry problems after parameter tuning.
citing papers explorer
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Robust Structure Learning of $k$-local Lindbladians
Protocol learns k-local Lindbladians to ε accuracy with Õ(n^{2k}/ε²) samples and projects to valid generators; improves to log n under sparsity assumptions.
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Rounding the Lov\'asz Theta Function with a Value Function Approximation
A new single-SDP rounding method for Lovász theta that provably recovers maximum weighted stable sets in generalized split graphs and other perfect graph subclasses via value function approximation and dynamic programming.
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Forward-Assisted Purification: A Spatiotemporal Framework Beyond Conventional Limits
Introduces forward-assisted purification via a new spatiotemporal framework that outperforms conventional static purification by up to 50x in copy efficiency and circumvents no-purification theorems for Bell states.
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New Bounds for Integer Flows and Verma Modules, via Denormalized Lorentzian Laurent Series
Denormalized Lorentzian Laurent series are defined and used to prove new bounds for integral flows on DAGs and weight-space dimensions in parabolic sl_{n+1} Verma modules.
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Data-driven discovery of polynomial ODEs with provably bounded solutions
SILAS jointly optimizes polynomial ODE vector fields and polynomial Lyapunov functions from data to produce models with provably bounded trajectories via compact absorbing sets.
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An algorithm for dynamical quantum optimal transport with applications to quantum chemistry
An interior-point method is introduced to compute dynamical quantum optimal transport geodesics on density matrices, shown to approximate some quantum chemistry problems after parameter tuning.