We propose to use wave function overlaps obtained from a quantum computer as inputs for the classical split-amplitude techniques, tailored and externally corrected coupled cluster, to achieve balanced treatment of static and dynamic correlation effects in molecular electronic structure simulations. By combining insights from statistical properties of matchgate shadows, which are used to measure quantum trial state overlaps, with classical correlation diagnostics, we can provide quantum resource estimates well into the classically no longer exactly solvable regime. We find that rather imperfect wave functions and remarkably low shot counts are sufficient to cure qualitative failures of plain coupled cluster singles doubles and to obtain chemically precise dynamic correlation energy corrections. We provide insights into which wave function preparation schemes have a chance of yielding quantum advantage, and we test our proposed method using overlaps measured on Google's Sycamore device.
We present the quantum-selected configuration interaction-tailored coupled-cluster (QSCI-TCC) method, a hybrid quantum-classical scheme that tailors coupled-cluster (CC) theory with a quantum-selected configuration interaction (QSCI) wave function. QSCI provides a scalable, shot-efficient approach to reconstructing the many-electron state prepared on quantum hardware on a classical computer. The resulting active-space CI coefficients, which are free from additive shot noise, are mapped to fixed cluster amplitudes within the tailored coupled-cluster framework, after which a conventional CC calculation optimizes the remaining amplitudes. This workflow embeds static (strong) correlation from the quantum device and subsequently recovers dynamical (weak) correlation, yielding a balanced description of both. The method is classically simulated and applied to the simultaneous O-H bond dissociation in H
2O and the triple-bond dissociation in N
2. QSCI-TCC and its perturbative-triples variant, QSCI-TCC(T), provide accurate results even where CCSD or CCSD(T) begin to break down. Shot-count tests for the N
2 (6e, 6o) active space demonstrate that, with the (c) correction, chemically sufficient precision (
≤1 kcal/mol) is achieved with only
1.0×105 shots in the strongly correlated regime (
r=2.2 Å) -- an order of magnitude fewer than required by an earlier matchgate-shadows implementation [J. Chem. Theory Comput., 20, 5068 (2024)]. By pairing resource-efficient quantum sampling with the CC theory, QSCI-TCC provides a promising pathway to quantum-chemical calculations of classically intractable systems.
We propose a practical method for accurately evaluating molecular total energies using a hybrid approach that integrates fault-tolerant quantum computers with classical computing. Our scheme consists of two complementary components: quantum dominant orbital selection (QDOS) and subspace dynamical correlation (SDC). QDOS extracts only the essential active orbitals from the complete active space (CAS) configuration interaction (CI) state on a quantum computer, yielding a compact active space suitable for classical CASCI calculations. SDC then evaluates dynamical-correlation corrections for the CASCI energy using this compact state, which remains tractable on classical machines. To demonstrate that the CAS energy obtained on a quantum computer can be post-corrected by SDC, we examine two frameworks: multireference perturbation theory and tailored coupled-cluster theory. Our scheme enables effective treatment of relatively large molecular systems by combining limited quantum and classical resources.
The central problem in the modern electronic structure theory is the calculation of cor- relation energy, possibly by an approach that would account for both static and dynamic correlation in an efficient, balanced and accurate way. In this thesis, I present a collection of methods that combine the effective treatment of dynamic correlation by the coupled cluster theory with density matrix renormalization group, a well-established technique for calculations of strongly correlated systems. The connection between them is achieved via the tailored coupled clusters (TCC) ansatz, which conveniently does not impose any ad- ditional computational costs. After the successful initial assessment, we developed more efficient implementations of these methods by employing the local approaches based on pair natural orbitals. This way, we extended the range of possible applications to larger systems with thousands of basis functions. To assess the accuracy of TCC as well as its local counterparts, we performed a variety of benchmark calculations ranging from small, yet challenging systems such as the nitrogen molecule or tetramethyleneethane diradical, to larger molecules like oxo-Mn(Salen) or Fe(II)-porphyrin model. 1
Introducing an active space approximation is inevitable for the quantum computations of chemical systems. However, this approximation ignores the electron correlations related to nonactive orbitals. Here, we propose a computational method for correcting quantum computing results using a well-established classical theory called coupled cluster theory. Our approach efficiently extracts the quantum state from a quantum device by computational basis tomography. The extracted expansion coefficients of the quantum state are embedded into the coupled cluster ansatz within the framework of the tailored coupled cluster method. We demonstrate the performance of our method by verifying the potential energy curves of LiH, H 2 O , and N 2 with a correlation-energy correction scheme. Our method demonstrates reasonable potential energy curves even when the standard coupled cluster fails. The sufficient numbers of measurements for tomography were also investigated. Furthermore, this method successfully estimated the activation energy of the Cope rearrangement reaction of 1,5-hexadiene together with perturbative triples correction. These demonstrations suggest that our approach has the potential for practical quantum chemical calculations using quantum computers. Published by the American Physical Society 2024
We combine classical heuristics with partial shadow tomography to enable efficient protocols for extracting information from correlated ab initio electronic systems encoded on quantum devices. By proposing the use of a correlation energy functional and sampling of a polynomial set of excitation amplitudes of the quantum state, we can demonstrate an almost two order of magnitude reduction in required number of shots for a given statistical error in the energy estimate, as well as observing a linear scaling to accessible system sizes. Furthermore, we find a high-degree of noise resilience of these estimators on real quantum devices, with up to an order of magnitude increase in the tolerated noise compared to traditional techniques. While these approaches are expected to break down asymptotically, we find strong evidence that these large system arguments do not prevent algorithmic advantage from these simple protocols in many systems of interest. We further extend this to consider the extraction of beyond-energetic properties by mapping to a coupled cluster surrogate model, as well as a natural combination within a quantum embedding framework. This embedding framework avoids the unstable self-consistent requirements of previous approaches, enabling application of quantum solvers to realistic correlated materials science, where we demonstrate the volume-dependence of the spin gap of Nickel Oxide.
Quantum-classical auxiliary-field quantum Monte Carlo (QC-AFQMC) is a promising route to using quantum computers for strongly correlated electronic structure problems, but its scalability is limited by a classical post-processing bottleneck: the measured quantum trial state must be used to evaluate overlaps, force biases, and local energies for many walkers throughout the AFQMC propagation. Existing matchgate-shadow approaches avoid the exponential cost of generic classical shadows, but their post-processing remains expensive for large systems. In this work, we show that particle-number-preserving fermionic shadows, implemented as orbital-rotation shadows, are able to drastically reduce QC-AFQMC post-processing costs. We derive efficient estimators for overlaps and their derivatives, giving
O(N3) scaling for overlaps and force biases and
O(N4) scaling for local energies per shadow and walker and with
O(N) Cholesky vector. For fixed normalized target determinants, we also prove that the overlap estimator is unbiased with variance upper bounded by
O(η), where
η is the particle number, yielding a sufficient budget of
O(η/ε2) ideal independent measurements for additive overlap error
ε. We combine these estimators with a novel virtual-correlation-energy treatment and a GPU implementation and demonstrate QC-AFQMC using orbital-rotation shadows. Performance projections for
π-conjugated molecules up to pentacene with a (22e, 22o) active space and 356 total orbitals show that the full classical post-processing workflow can be completed in slightly more than two days on 8
×A100 graphics processing units (GPUs). These results significantly reduce classical post-processing costs for QC-AFQMC and motivate further improvements in preparation and measurement of the trial state on quantum hardware.