Quantum Simulation

By I. Georgescu, Sahel Ashhab, Franco Nori. Quantum Atom Optics, 2013

2,143 citations recorded by the source corpus.

Simulating quantum mechanics is known to be a difficult computational problem, especially when dealing with large systems. However, this difficulty may be overcome by using some controllable quantum system to study another less controllable or accessible quantum system, i.e., quantum simulation. Quantum simulation promises to have applications in the study of many problems in, e.g., condensed-matter physics, high-energy physics, atomic physics, quantum chemistry and cosmology. Quantum simulation could be implemented using quantum computers, but also with simpler, analog devices that would require less control, and therefore, would be easier to construct. A number of quantum systems such as neutral atoms, ions, polar molecules, electrons in semiconductors, superconducting circuits, nuclear spins and photons have been proposed as quantum simulators. This review outlines the main theoretical and experimental aspects of quantum simulation and emphasizes some of the challenges and promises of this fast-growing field.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/29fef61b3d7c3fcbd70e5055c17743173e317d67

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In Atomic and Molecular Physics, and Optics

Citations in the corpus

Challenges and opportunities in quantum machine learning (2022, background): “[129] Iulia M Georgescu, Sahel Ashhab, and Franco Nori, “Quantum simulation,” Reviews of Modern Physics 86, 153 (2014).”
t|ket⟩: a retargetable compiler for NISQ devices (2020, background): “For some tasks, notably the simulation of condensed-matter physics, the abstract structure of the problem may be suﬃciently similar to the physical structure of the device that translation from one to the other is natural and (relatively) straightforward [4].”
Ising machines as hardware solvers of combinatorial optimization problems (2022, methodology): “The similarity of the underlying energy model of Boltzmann-machine hardware accelerators suggests that such technologies could be adapted to act as Ising solvers.”
Quantum computing for finance: Overview and prospects (2018, background): “It would have been interesting to talk about how quantum technologies can be relevant to the blockchain and cryptocurrencies [82], or to discuss quantum finance [5, 6], quantum money [83], the impact of quantum cryptography in the security of financial transactions [15, 84], and the applications of ”
Diagnosing Barren Plateaus with Tools from Quantum Optimal Control (2021, background): “[4] Iulia M Georgescu, Sahel Ashhab, and Franco Nori.”