Searcharxiv⌕ Search

arXiv · 2609.22729

Can Chemically Inspired Parameter Initialization Mitigate Barren Plateaus in Variational Quantum Eigensolvers?

Abstract

Recent advances in the variational quantum eigensolver (VQE) have strengthened its promise for molecular electronic-structure calculations on near-term noisy intermediate-scale quantum (NISQ) devices. However, barren plateaus (BPs) remain a major obstacle to scaling VQE, as vanishing gradients can severely obstruct optimization at large scale. While most BP studies focus on randomly initialized circuits and global gradient behavior, practical quantum chemistry VQE typically uses chemically motivated initializations and local optimization around HF- or MP2-derived states. Although chemically informed initializations are widely expected to improve VQE trainability, how they mitigate local barren plateaus remains unclear. We therefore study the occurrence of local barren plateaus in molecular UCCSD-VQE, considering both chemically motivated initialization points and iterates along the corresponding optimization trajectories. In the benchmarks considered here, chemically initialized starting points and variational trajectories show polynomial decay of local gradient variance with system size instead of the exponential BP-like decay observed for random controls, indicating that chemical initialization mitigates barren plateaus in the local optimization regions and highlights the trainability advantage of chemically motivated VQE strategies.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zhangyu Yang, Jinzhao Sun, Jianpeng Chen, Weitang Li, Zhigang Shuai. 2026-09-19. Can Chemically Inspired Parameter Initialization Mitigate Barren Plateaus in Variational Quantum Eigensolvers?. https://arxiv.org/abs/2609.22729

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

The NewMag crystal-field code for f-element systems: Implementation for extended active spaces, second-order correlated energies, and generalisation to fn configurations

We report a massive update of the NewMag program, which enables to extract Stevens crystal-field parameters (CFPs) after relativistic and multiconfigurational calculations are performed. The code can now post-treat ORCA and OpenMolcas outputs that contain state-average complete active space self-consistend field (SA-CASSCF) calculations with minimal or extended active spaces, second-order NEVPT2 or CASPT2 calculations, and spin-orbit configuration interaction (SOCI) calculations. Stevens parameters are extracted following the original Stevens convention with the so-called "extended" parameters. Rotation invariant indicators are also computed, after applying a correction of the parameter values to ensure normalization, following Rudowicz. At the SOCI level, the spin-orbit coupling (SOC) constant is also extracted within a spherical approximation of the SOC operator. For all the reference calculation levels, the model spectrum is reconstructed, allowing a direct assessment of its quality. The reported implementation is successfully applicable to f-element systems with a non-void, non-half-filled/empty or non-full f shell, that is for f^n configurations with n != 0, != 7 and != 14. Similarities and differences with the SINGLE_ANISO and AILFT codes are discussed. With selected examples, we showcase the interest of determining CFPs in f-element systems to understand their magnetic and optical properties in general, and more specifically the added value of NewMag. Finally, application of this approach to d-element systems is discussed, to reveal when it readily and successfully applies and when it may fail in reproducing satisfactorily the ab initio energies.

physics.chem-ph↗

Fortuitous Cancellation of Competing Effects in the Free Energy of Water Autoionization: Long-Range Electrostatics, System Size, and Nuclear Quantum Effects

Few molecular processes are more fundamental to chemistry than the autoionization of water, whose equilibrium constant, $K_w \approx 10^{-14}$, underlies acid-base equilibria and the chemistry of life. Yet the molecular origins of the free energy cost of forming and separating ions remain incompletely understood. Efforts to explain it have been limited by the difficulty of modeling water reactivity in sufficient detail. Here we combine machine learning interatomic potentials (MLIPs) with spectral adaptive biasing force enhanced sampling to connect proton transfer and water wire configurations to the underlying free energy landscape. We identify competing influences of long-range electrostatics, system size, temperature, and nuclear quantum motion on the predicted ionization thermodynamics. The free energy surface extends from neutral water to ions separated beyond the solvent-separated ion pair (SSIP). It reveals a transition state in which a proton is shared between the second and third molecules of a three-membered water wire. The contact ion pair is unstable and the SSIP only weakly metastable, so determining pK$_w$ requires sampling longer wires. Long-range electrostatics raise the free energy at ion separations beyond $3\,\mathrm{\mathring{A}}$. Models with comparable force errors give substantially different free energy profiles in this region. Increasing system size lowers the calculated pK$_w$, while nuclear quantum effects bring it closer to experiment and reproduce the higher pK$_w$ of D$_2$O relative to H$_2$O. These results establish a baseline for interpreting thermodynamic results from MLIP simulations in which charged and polar groups react and diffuse in finite cells. Our analysis also explains how cancellation among competing effects can yield ionization constants close to experiment even when simulations omit several physical contributions.

physics.chem-ph↗

GPU implementation of mixed quantum-classical Liouville molecular dynamics without momentum jump

We implemented on GPU a mixed quantum-classical Liouville molecular dynamics simulation based on a momentum-jump-free theory. The trajectory spawning that was previously implemented on CPU for sampling enhancement was eliminated to avoid the overhead of thread divergence and dynamic memory allocation on the GPU. The method was applied to a three-dimensional spin-boson model and a three-mode model of $S_2 \to S_1$ internal conversion in pyrazine involving a conical intersection. A speedup of an order of magnitude compared to the CPU computation with spawning was achieved, as well as a linear scaling with respect to the number of sampling trajectories.

physics.chem-ph↗