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Simulating quantum many-body systems is a challenging but very relevant task for many fields of physics, ranging from material science and quantum chemistry to particle physics. Quantum algorithms can solve this problem more efficiently than classical methods, making quantum simulation one of the most promising practical applications of quantum computers. In terms of specific quantum hardware, we have a large expertise with atomic platforms, where quantum information is encoded in the internal electronic states of neutral atoms trapped in optical potentials, and processed using laser pulses. On the software side, we investigate both analog as well as digital quantum simulation algorithms, and focus on applications to condensed-matter and high-energy physics. Below you can find a short summary about these two approaches, as well as more detailed information about the specific research lines we follow in the group.
Analog quantum simulators are designed to mimic the properties of other, less accessible, quantum many-body systems, by engineering in particular tailored Hamiltonians, which can be controlled in great detail using atomic and optical techniques. Although less flexible, they are more robust to errors than their digital counterparts.
In our group, we use neutral atoms trapped in optical lattices and tweezer arrays to emulate many-body Hamiltonians relevant in condensed-matter and high-energy physics. We focus on Hamiltonian engineering using tools from theoretical atomic physics, develop equilibrium and non-equilibrium quantum simulation protocols, and benchmark them using tensor network methods.
Digital quantum simulation is one of the most promising near-term applications of quantum computers. In this case, state preparation or time evolution under a given Hamiltonian is implemented through a quantum circuit built from a universal set of quantum gates, allowing to target more complicated models than analog devices.
In our group, we develop quantum computing architectures to investigate quantum many-body physics, where we consider an end-to-end holistic approach to the problem. This includes the co-design of tailored quantum processors and hardware-efficient quantum algorithms, as well as novel formulations and encodings for the simulated theories.
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