Algorithms · Variational quantum eigensolver
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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- Record typeLiterature reference
- Reference implementationprojection_based_embedding
- Reported costNot stated by the sources read
- Papers1
A part this method uses, worked through
This page says combine the variational quantum eigensolver (VQE) with density functional theory
— here is a concrete, runnable instance of it.
VQE on a 2-qubit transverse-field Ising Hamiltonian
2 qubits, H = Z⊗Z + 0.5*(X⊗I + I⊗X), a stated toy Hamiltonian (not a molecule), minimised with a hardware-efficient ansatz.
Where it ends up
- 1043%
- 0143%
- 007%
- 117%
At these angles the ansatz's energy ⟨H⟩ reaches E0 = −√2, the Hamiltonian's exact ground energy; a real VQE run reaches these angles by repeating measure-the-energy then update-the-angles, not by a closed-form solution.
Open this part in StudioSimulate 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.
TakesNothingWhat joins here
No input port at this edge: the record publishes no gate sequence and no register, so there is nothing here to read one off — and unlike a declared hole, nothing has been recorded about what belongs here.
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ReturnsNothingWhat joins here
No output port at this edge: the record publishes no gate sequence and no register, so there is nothing here to read one off — and unlike a declared hole, nothing has been recorded about what belongs here.
Nothing in the Atlas meets this end.
This record publishes no gate sequence and no register, so there is nothing here to read an interface off. Absent rather than empty. See all 152 →
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 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 demonstration this record covers states no bound either. The complexity field is therefore left empty on purpose rather than filled with a bound written from memory.).
TakesNothingWhat joins here
No input port at this edge: the record publishes no gate sequence and no register, so there is nothing here to read one off — and unlike a declared hole, nothing has been recorded about what belongs here.
Nothing in the Atlas meets this end.
ReturnsNothingWhat joins here
No output port at this edge: the record publishes no gate sequence and no register, so there is nothing here to read one off — and unlike a declared hole, nothing has been recorded about what belongs here.
Nothing in the Atlas meets this end.
This record publishes no gate sequence and no register, so there is nothing here to read an interface off. Absent rather than empty. See all 152 →
- Record type
- Literature reference
- Reference implementation
- projection_based_embedding
- Reported cost
- Not stated by the sources read
- Complexity 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 demonstration this record covers states no bound either. The complexity field is therefore left empty on purpose rather than filled with a bound written from memory.
- Circuit
- Not supplied
This record is not a concrete circuit.
Quantum vs classical
Classical baseline
Compare Variational quantum eigensolver with the strongest classical method for the same instance, input budget, and output metric.
Quantum claim
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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 demonstration this record covers states no bound either. The complexity field is therefore left empty on purpose rather than filled with a bound written from memory.
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
This is a literature reference record, not an executable circuit.A reference record, not runnable source. Leona cannot execute it, so it cannot be saved to your Library as a circuit.
Where this sits
This record is named by the layer graph at:
- 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.
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References
- Quantum Embedding Method for the Simulation of Strongly Correlated Systems on Quantum Computers
Max Rossmannek, Fabijan Pavošević, Angel Rubio, Ivano Tavernelli · 2023
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.