5 papers
Efficient Learning of Structured Quantum Circuits via Pauli Dimensionality and Sparsity
Sabee Grewal, Daniel Liang
We study the problem of efficiently learning an unknown -qubit unitary channel in diamond distance given query access. We present a general framework showing that if Pauli opera…
Agnostic Tomography of Stabilizer Product States
Sabee Grewal, Vishnu Iyer, William Kretschmer +1
We define a quantum learning task called agnostic tomography, where given copies of an arbitrary state and a class of quantum states , the goal is to output a suc…
Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates
Sabee Grewal, Vishnu Iyer, William Kretschmer +1
We give a pair of algorithms that efficiently learn a quantum state prepared by Clifford gates and non-Clifford gates. Specifically, for an -qubit state …
Tolerant Testing of Stabilizer States with Mixed State Inputs
Vishnu Iyer, Daniel Liang
We study the problem of tolerant testing of stabilizer states. In particular, we give the first such algorithm that accepts mixed state inputs. Formally, given a mixed state t…
Hamiltonian Locality Testing via Trotterized Postselection
John Kallaugher, Daniel Liang
The (tolerant) Hamiltonian locality testing problem, introduced in [Bluhm, Caro,Oufkir `24], is to determine whether a Hamiltonian is -close to being -local (…