131 citations · 1.1k across the 58 of their papers we have counts for
63 papers
Learning SYK Hamiltonians
Anurag Anshu, Srinivasan Arunachalam, Sitan Chen +1
We study the problem of learning the dense Sachdev--Ye--Kitaev (SYK) Hamiltonian from copies of its Gibbs state. Existing algorithms for Hamiltonian learning typically rely on geom…
Depth-1 expanders on the unitary group and applications
Anurag Anshu, Shankar Balasubramanian, Jonas Haferkamp +2
We construct a constant-degree and constant-gap quantum expander on qubits where each unitary can be implemented by a depth- and 1D circuit of Pauli or CNOT gates. We provid…
Classical Adversarial Fault-Tolerance and PCPs
Anurag Anshu, Nikolas P. Breuckmann, Louis Golowich +2
We show how to compile an arbitrary classical circuit into a fault-tolerant circuit, which performs the desired computation even when an almost-linear number of bits are adversaria…
Randomness compression in communication networks
Yukari Uchibori, Alice Zheng, Anurag Anshu +1
Given a correlation generated by a (possibly quantum) communication network, we study the amount of shared randomness required to generate it. We develop a novel upper bound for ap…
An energy-based uncertainty principle and low-energy state preparation
Anurag Anshu
Preparing low-energy states of many-body Hamiltonians is a central challenge in quantum computing, quantum complexity, and condensed matter physics. Existing approaches often get t…
Learning quantum Gibbs states locally and efficiently
Chi-Fang Chen, Anurag Anshu, Quynh T. Nguyen
Learning the Hamiltonian underlying a quantum many-body system in thermal equilibrium is a fundamental task in quantum learning theory and experimental sciences. To learn the Gibbs…