arXiv subjects

Viktor Khinevich

Publications and source records attributed to Viktor Khinevich.

5 recordsLinked to original sources

arXiv2026

Symmetry-Adapted State Preparation for Quantum Chemistry on Fault-Tolerant Quantum Computers

We present systematic and resource-efficient constructions of continuous symmetry projectors, particularly $U(1)$ particle number and $SU(2)$ total spin, tailored for fault-tolerant quantum computations. Our approach employs a linear combination of unitaries (LCU) as well as generalized quantum signal processing (GQSP and GQSVT) to implement projectors. These projectors can then be coherently applied as state filters prior to quantum phase estimation (QPE). We analyze their asymptotic gate complexities for explicit circuit realizations. For the particle number and $S_z$ symmetries, GQSP offers favorable resource usage features owing to its low ancilla qubit requirements and robustness to finite precision rotation gate synthesis. For the total spin projection, the structured decomposition of $\hat{P}_{S,M_S}$ reduces the projector T gate count. Numerical simulations show that symmetry filtering substantially increases the QPE success probability, leading to a lower overall cost compared to that of unfiltered approaches across representative molecular systems. Resource estimates further indicate that the cost of symmetry filtering is $3$ to $4$ orders of magnitude lower than that of the subsequent phase estimation step This advantage is especially relevant in large, strongly correlated systems, such as FeMoco, a standard strongly correlated open-shell benchmark. For FeMoco, the QPE cost is estimated at ${\sim}10^{10}$ T gates, while our symmetry projector requires only ${\sim}10^{6}$--$10^{7}$ T gates. These results establish continuous-symmetry projectors as practical and scalable tools for state preparation in quantum chemistry and provide a pathway toward realizing more efficient fault-tolerant quantum simulations.

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arXiv2025

Quantum Power Iteration Unified Using Generalized Quantum Signal Processing

We propose a unifying framework for the state preparation using quantum power method algorithms based on generalized quantum signal processing (GQSP). We apply GQSP to realize quantum analogs of classical power iteration, power Lanczos, inverse iteration, and folded spectrum methods, all within a single coherent framework. GQSP allows efficient realization of methods that require complex polynomials, while avoiding the limitations of approaches based on linear combinations of time-evolution operators. Our constructions, including a Trotter-decomposition-free quantum inverse iteration, achieve near-optimal query scaling, together with reduced qubit requirements. The same formalism yields a quantum folded spectrum method for excited state preparation that avoids explicitly forming powers of the Hamiltonian or performing variational optimization. We provide a theoretical analysis of success probabilities and resource scaling, and we validate the methods numerically using molecular Hamiltonians. The results show that quantum power Lanczos lowers the computational cost and provides robust convergence compared to naive quantum power iteration. Our findings reveal that GQSP-based implementations of power methods combine scalability, flexibility, and robust convergence, paving the way for practical initial state preparations on fault-tolerant quantum devices.

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arXiv2025

Enhancing quantum computations with the synergy of auxiliary field quantum Monte Carlo and computational basis tomography

We introduce QC-CBT-AFQMC, a hybrid algorithm that incorporates computational basis tomography (CBT) into the quantum-classical auxiliary-field quantum Monte Carlo (QC-AFQMC) method proposed by Huggins et al. [Nature 603, 416-420 (2022)], replacing the use of classical shadows. While the original QC-AFQMC showed high accuracy for quantum chemistry calculations, it required exponentially costly post-processing. Subsequent work using Matchgate shadows [Commun. Math. Phys. 404, 629 (2023)] improved scalability, but still suffers from prohibitive computational requirements that limit practical applications. Our QC-CBT-AFQMC approach uses shallow Clifford circuits with a quadratic reduction of two-qubit gates over the original algorithm, significantly reducing computational requirements and enabling accurate calculations under limited measurement budgets. We demonstrate its effectiveness on the hydroxyl radical, ethylene, and nitrogen molecule, producing potential energy curves that closely match established benchmarks. We also examine the influence of CBT measurement counts on accuracy, showing that subtracting the active space AFQMC energy mitigates measurement-induced errors. Furthermore, we apply QC-CBT-AFQMC to estimate reaction barriers in [3+2]-cycloaddition reactions, achieving agreement with high-level references and successfully incorporating complete basis set extrapolation techniques. These results highlight QC-CBT-AFQMC as a practical quantum-classical hybrid method that bridges the capabilities of quantum devices and accurate chemical simulations.

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arXiv2024

Chebyshev Approximated Variational Coupled Cluster for Quantum Computing

We propose an approach to approximately implement the variational coupled cluster (VCC) theory on quantum computers, which struggles with exponential scaling of computational costs on classical computers. To this end, we employ expanding the exponential cluster operator using Chebyshev polynomials and introduce two methods: the Chebyshev approximated VCC (C$^d$-VCC) and the Hermitian-part Chebyshev approximated VCC (HC$^d$-VCC), where $d$ indicates the maximum degree of the Chebyshev polynomials. The latter method decomposes the cluster operator into anti-Hermitian and Hermitian parts, with the anti-Hermitian part represented by the disentangled unitary coupled cluster ansatz and the Hermitian part approximated using Chebyshev expansion. We illustrate the implementation of the HC$^d$-VCC in a quantum circuit using the quantum singular value transformation technique. Numerical simulations show that the C$^d$-VCC rapidly converges to the exact VCC with increasing truncation degree $d$, and the HC$^d$-VCC effectively reduces the Chebyshev expansion error compared to the C$^d$-VCC. The HC$^d$-VCC method for realizing non-unitary coupled cluster wave functions on quantum computers is expected to be useful for initial state preparation on quantum computers and efficient tomography of the quantum state for post-processing on classical computers after quantum computations.

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arXiv2024

Coupled cluster method tailored with quantum computing

Introducing an active space approximation is inevitable for the quantum computations of chemical systems. However, this approximation ignores the electron correlations related to non-active 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, H2O, and N2 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.

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