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Scalable quantum dynamics compilation via quantum machine learning
Yuxuan Zhang, Roeland Wiersema, Juan Carrasquilla +2
Quantum dynamics compilation is an important task for improving quantum simulation efficiency: It aims to synthesize multi-qubit target dynamics into a circuit consisting of as few…
Observation of a non-Hermitian supersonic mode on a trapped-ion quantum computer
Yuxuan Zhang, Juan Carrasquilla, Yong Baek Kim
Quantum computers have long been anticipated to excel in simulating quantum many-body physics. While most previous work has focused on Hermitian physics, we demonstrate the power o…
The statistical mechanics and machine learning of the -Rényi ensemble
Andrew Jreissaty, Juan Carrasquilla
We study the statistical physics of the classical Ising model in the so-called -Rényi ensemble, a finite-temperature thermal state approximation that minimizes a modified free e…
Beyond-classical computation in quantum simulation
Andrew D. King, Alberto Nocera, Marek M. Rams +60
Quantum computers hold the promise of solving certain problems that lie beyond the reach of conventional computers. However, establishing this capability, especially for impactful…
Geodesic Algorithm for Unitary Gate Design with Time-Independent Hamiltonians
Dylan Lewis, Roeland Wiersema, Juan Carrasquilla +1
Larger multi-qubit quantum gates allow shallower, more efficient quantum circuits, which could decrease the prohibitive effect of noise on algorithms for noisy intermediate-scale q…
Characterization of overparametrization in the simulation of realistic quantum systems
Matthew Duschenes, Juan Carrasquilla, Raymond Laflamme
Quantum computing devices require exceptional control of their experimental parameters to prepare quantum states and simulate other quantum systems. Classical optimization procedur…