10 papers
Hierarchical Learning for Quantum ML: Novel Training Technique for Large-Scale Variational Quantum Circuits
Hrant Gharibyan, Vincent Su, Hayk Tepanyan
We present hierarchical learning, a novel variational architecture for efficient training of large-scale variational quantum circuits. We test and benchmark our technique for distr…
Toward simulating Superstring/M-theory on a quantum computer
Hrant Gharibyan, Masanori Hanada, Masazumi Honda +1
We present a novel framework for simulating matrix models on a quantum computer. Supersymmetric matrix models have natural applications to superstring/M-theory and gravitational ph…
The Python's Lunch: geometric obstructions to decoding Hawking radiation
Adam R. Brown, Hrant Gharibyan, Geoff Penington +1
According to Harlow and Hayden [arXiv:1301.4504] the task of distilling information out of Hawking radiation appears to be computationally hard despite the fact that the quantum st…
A characterization of quantum chaos by two-point correlation functions
Hrant Gharibyan, Masanori Hanada, Brian Swingle +1
We propose a characterization of quantum many-body chaos: given a collection of simple operators, the set of all possible pair-correlations between these operators can be organized…
Quantum Virtual Cooling
Jordan Cotler, Soonwon Choi, Alexander Lukin +10
We propose a quantum information based scheme to reduce the temperature of quantum many-body systems, and access regimes beyond the current capability of conventional cooling techn…
The Case of the Missing Gates: Complexity of Jackiw-Teitelboim Gravity
Adam R. Brown, Hrant Gharibyan, Henry W. Lin +3
The Jackiw-Teitelboim (JT) model arises from the dimensional reduction of charged black holes. Motivated by the holographic complexity conjecture, we calculate the late-time rate o…