Primary source: it states the projection-based embedding method for combining VQE with DFT, the resulting VQE-in-DFT method, its implementation on a real quantum device, and its use to simulate triple-bond breaking in butyronitrile. Consult it for the device used, the number of qubits, the accuracy achieved, and how the strongly correlated fragment was selected, none of which the abstract states.
arxiv.org/abs/2302.03052 ↗Projection-based embedding for VQE-in-DFT
Simulate strongly correlated chemical systems on near-term quantum hardware, whose noise and limited size otherwise confine such simulations to small chemical systems, by embedding a quantum treatment of a strongly correlated fragment within a larger classical calculation.
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Simulate strongly correlated chemical systems on near-term quantum hardware, whose noise and limited size otherwise confine such simulations to small chemical systems, by embedding a quantum treatment of a strongly correlated fragment within a larger classical calculation. Rossmannek, Pavošević, Rubio and Tavernelli combine the variational quantum eigensolver (VQE) with density functional theory (DFT) through a quantum embedding approach, using the projection-based embedding method to couple the two — a method the authors state is not limited to VQE. The resulting VQE-in-DFT method treats a strongly correlated fragment of a chemical system with VQE while treating the remainder with DFT, addressing the current limitation of near-term quantum devices to small chemical systems. The authors report implementing the method efficiently on a real quantum device and applying it to simulate the triple-bond breaking process in butyronitrile. They present the results as showing that the developed method is a promising approach for simulating systems with a strongly correlated fragment on a quantum computer, and state that the developments and their implementation will benefit chemical areas including computer-aided drug design and the study of metalloenzymes with a strongly correlated fragment.
Circuit & simulation
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- Estimate a Hamiltonian's ground-state energy Slot
Takes A Hermitian reachable as a sum of terms, as sparse-access oracles or as a block-encoding; a way to prepare trial states, and — for the methods that need it — a trial state whose overlap with the ground state is not negligible; a target additive error and a confidence . Returns A scalar estimate of the lowest eigenvalue with a stated additive-error guarantee, plus the run or query budget it consumed. Whether that estimate is also a rigorous upper bound is a property of the method and is not promised by the slot.
How it works
Rossmannek, Pavošević, Rubio and Tavernelli combine the variational quantum eigensolver (VQE) with density functional theory (DFT) through a quantum embedding approach, using the projection-based embedding method to couple the two — a method the authors state is not limited to VQE. The resulting VQE-in-DFT method treats a strongly correlated fragment of a chemical system with VQE while treating the remainder with DFT, addressing the current limitation of near-term quantum devices to small chemical systems. The authors report implementing the method efficiently on a real quantum device and applying it to simulate the triple-bond breaking process in butyronitrile. They present the results as showing that the developed method is a promising approach for simulating systems with a strongly correlated fragment on a quantum computer, and state that the developments and their implementation will benefit chemical areas including computer-aided drug design and the study of metalloenzymes with a strongly correlated fragment. The Classiq library carries this subject under applications · chemistry. The sources read state no complexity bound for this record (The abstract of arXiv:2302.03052, the only source read for this record, states no cost, running time, qubit count, gate count or speedup bound anywhere in it. Its claims are architectural and qualitative: it says quantum computing "has emerged as a promising platform for simulating strongly correlated systems in chemistry" while near-term hardware limitations mean "their application is currently limited only to small chemical systems", and that the developed VQE-in-DFT method "is then implemented efficiently on a real quantum device" without stating what that efficiency consists of in qubits, gates, or time. The Classiq index entry for applications/chemistry/projection_based_embedding gives a directory path and a single file, projected_based_embedding_tutorial.ipynb, and states no bound either. The complexity field is therefore left empty on purpose rather than filled with a bound written from memory.).
Implementation
ALGORITHM: Projection-based embedding for VQE-in-DFT
PROBLEM: Simulate strongly correlated chemical systems on near-term quantum hardware, whose noise and limited size otherwise confine such simulations to small chemical systems, by embedding a quantum treatment of a strongly correlated fragment within a larger classical calculation.
IDEA: Rossmannek, Pavošević, Rubio and Tavernelli combine the variational quantum eigensolver (VQE) with density functional theory (DFT) through a quantum embedding approach, using the projection-based embedding method to couple the two — a method the authors state is not limited to VQE. The resulting VQE-in-DFT method treats a strongly correlated fragment of a chemical system with VQE while treating the remainder with DFT, addressing the current limitation of near-term quantum devices to small chemical systems. The authors report implementing the method efficiently on a real quantum device and applying it to simulate the triple-bond breaking process in butyronitrile. They present the results as showing that the developed method is a promising approach for simulating systems with a strongly correlated fragment on a quantum computer, and state that the developments and their implementation will benefit chemical areas including computer-aided drug design and the study of metalloenzymes with a strongly correlated fragment.
REPORTED COST: Not stated by the sources read
BASIS: The abstract of arXiv:2302.03052, the only source read for this record, states no cost, running time, qubit count, gate count or speedup bound anywhere in it. Its claims are architectural and qualitative: it says quantum computing "has emerged as a promising platform for simulating strongly correlated systems in chemistry" while near-term hardware limitations mean "their application is currently limited only to small chemical systems", and that the developed VQE-in-DFT method "is then implemented efficiently on a real quantum device" without stating what that efficiency consists of in qubits, gates, or time. The Classiq index entry for applications/chemistry/projection_based_embedding gives a directory path and a single file, projected_based_embedding_tutorial.ipynb, and states no bound either. The complexity field is therefore left empty on purpose rather than filled with a bound written from memory.
DEMONSTRATED BY: the Classiq library entry applications/chemistry/projection_based_embedding
PRIMARY SOURCE: Max Rossmannek, Fabijan Pavošević, Angel Rubio, Ivano Tavernelli (2023), Quantum Embedding Method for the Simulation of Strongly Correlated Systems on Quantum Computers — https://arxiv.org/abs/2302.03052
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Quantum vs classical
Classical baseline
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Quantum claim
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