SearcharxivSearch

arXiv subjects

Vincent Beltrani

Publications and source records attributed to Vincent Beltrani.

3 recordsLinked to original sources

Sample-based quantum diagonalization approach for open-shell transition-metal complexes in gas and implicit-solvent

Open-shell $3d$ transition-metal complexes challenge electronic-structure methods because competing spin states, charge transfer, and solvation jointly determine their energetics. Here, we combine sample-based quantum diagonalization (SQD) with the integral-equation-formalism polarizable continuum model (IEF-PCM), extending SQD to correlated open-shell transition-metal systems in a dielectric environment. We investigate the octahedrally coordinated $\mathrm{[Co(H_2O)_5CO_2]^{2+/3+}}$ complex across two oxidation states, four spin multiplicities, and a metal-ligand dissociation coordinate. We study the Co(III) singlet and quintet states and the Co(II) doublet and quartet states, incorporating open-shell references into SQD-IEF-PCM through an outer self-consistent reaction-field loop. Using samples collected on an IBM Heron quantum processor and active spaces of up to 50 qubits, SQD reproduces coupled-cluster and heat-bath configuration-interaction benchmarks within the same active space in the gas phase and implicit solvent, with a largest observed deviation below 9 $mE_h$. Along the dissociation coordinate of high-spin quintet $\mathrm{[Co(H_2O)_5CO_2]^{3+}}$, SQD resolves an avoided crossing caused by internal charge transfer; this feature is absent in the singlet and the lower oxidation state of the complex. Relative to the gas phase, implicit solvation stabilizes for the quintet state the neutral CO$_2$ dissociation and suppresses the avoided-crossing feature. To our knowledge, this is the first hardware demonstration of SQD for an open-shell $3d$ transition-metal complex in gas phase and implict solvent. These results establish SQD as a robust quantum-centric approach for transition-metal chemistry where spin state ordering, charge transfer, and environmental effects are strongly intertwined.

quant-ph

Quantum-enhanced satellite image classification

We demonstrate the application of a quantum feature extraction method to enhance multi-class image classification for space applications. By harnessing the dynamics of many-body spin Hamiltonians, the method generates expressive quantum features that, when combined with classical processing, lead to quantum-enhanced classification accuracy. Using a strong and well-established ResNet50 baseline, we achieved a maximum classical accuracy of 83%, which can be improved to 84% with a transfer learning approach. In contrast, applying our quantum-classical method the performance is increased to 87% accuracy, demonstrating a clear and reproducible improvement over robust classical approaches. Implemented on several of IBM's quantum processors, our hybrid quantum-classical approach delivers consistent gains of 2-3% in absolute accuracy. These results highlight the practical potential of current and near-term quantum processors in high-stakes, data-driven domains such as satellite imaging and remote sensing, while suggesting broader applicability in real-world machine learning tasks.

quant-ph

Exploring the top and bottom of the quantum control landscape

A controlled quantum system possesses a search landscape defined by the target physical objective as a function of the controls. This paper focuses on the landscape for the transition probability Pif between the states of a finite level quantum system. Traditionally, the controls are applied fields; here we extend the notion of control to also include the Hamiltonian structure, in the form of time independent matrix elements. Level sets of controls that produce the same transition probability value are shown to exist at the bottom Pif = 0.0 and top Pif = 1.0 of the landscape with the field and/or Hamiltonian structure as controls. We present an algorithm to continuously explore these level sets starting from an initial point residing at either extreme value of Pif . The technique can also identify control solutions that exhibit the desirable properties of (a) robustness at the top and (b) the ability to rapidly rise towards an optimal control from the bottom. Numerical simulations are presented to illustrate the varied control behavior at the top and bottom of the landscape for several simple model systems.

physics.chem-ph