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From the 1 of 7 linked papers with an AI index.

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7 papers

cond-mat.stat-mech2026

Equivariant learning of a transferable three-dimensional classical density functional

Bingqing Cheng

Liquids exhibit collective behavior that depends sensitively on thermodynamic conditions, interfaces and confinement, yet predicting each new state commonly requires a separate ato…

quant-ph2026

Restrictions on non-Clifford fault tolerance and ruling out beyond-SQL quantum metrology

Constantin Cedillo Vayson de Pradenne, Ishaan Kannan, Harald Putterman +1

The paper proves limits on transversal non‑Clifford gates in stabilizer codes, showing these constraints prevent fault‑tolerant transversal sensing that would surpass the standard…

quant-ph2026

Learning Arbitrary Lindbladians with Quantum Error Correction

Nikita Romanov, Petr Ivashkov, Weiyuan Gong +4

We study ansatz-free Lindbladian learning, the problem of reconstructing the generator of an open quantum system without prior knowledge of its Hamiltonian or dissipator structures…

quant-ph2026

Exponential speedups in fault-tolerant processing of quantum experiments

Ishaan Kannan, Harald Putterman, Jordan Cotler

Quantum information processing has the potential to substantially enhance how we learn from physical experiments, but coupling a quantum processor to an experimental sample introdu…

quant-ph2026

Quantum Advantage for Sensing Properties of Classical Fields

Jordan Cotler, Daine L. Danielson, Ishaan Kannan

Modern precision experiments often probe unknown classical fields with bosonic sensors in quantum-noise-limited regimes where vacuum fluctuations limit conventional readout. We int…

quant-ph2026

Noisy Quantum Learning Theory

Jordan Cotler, Weiyuan Gong, Ishaan Kannan

We develop a framework for learning from noisy quantum experiments in which fault-tolerant devices access uncharacterized systems through noisy couplings. Introducing the complexit…