From the 2 of 9 linked papers with an AI index.
9 papers
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…
When quantum thermal states look classical
Harald Putterman, Alexander Zlokapa, Jordan Cotler
The paper analyzes how quantum Gibbs states retain classical properties such as lack of entanglement and magic at finite temperatures, establishing a hierarchy of classical‑to‑quan…
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…
Dynamics of learning to integrate in linear recurrent neural networks
Blake Bordelon, Jordan Cotler, Cengiz Pehlevan +1
Learning recurrent connectivity that supports memory over long intrinsic timescales is a basic problem in the theory of dynamical computation. While continuous attractor and integr…
Learning Hamiltonians at Long Times
Constantin Cedillo Vayson de Pradenne, Jordan Cotler, Hsin-Yuan Huang
We study the problem of learning an unknown -qubit Hamiltonian from for a single time , where may be arbitrarily large. For broad families of local Ham…
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…