Physics-Informed Neural Quantum Control for Rovibrational Photoassociation in a Morse Molecular System
- URL: http://arxiv.org/abs/2606.29610v2
- Date: Mon, 06 Jul 2026 13:58:19 GMT
- Title: Physics-Informed Neural Quantum Control for Rovibrational Photoassociation in a Morse Molecular System
- Abstract summary: We present a framework for rovibrational photoassociation in a Morse molecular system.<n>The proposed method combines neural-network-based laser-field generation with differentiable quantum propagation.<n>Results establish the PINQC framework as a promising computational tool for molecular photoassociation.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We present a Physics-Informed Neural Quantum Control (PINQC) framework for rovibrational photoassociation in a Morse molecular system. The proposed method combines neural-network-based laser-field generation with differentiable quantum propagation, allowing optimized laser pulses to be obtained directly from the underlying quantum dynamics without requiring external training data. The optimized control fields efficiently transfer an initially continuum-like Gaussian wave packet into the vibrational ground-state level, promoting continuum-to-bound population transfer through coherent rovibrational dynamics. The resulting photoassociation process involves both vibrational stabilization and rotational redistribution arising naturally from dipole-induced couplings between neighboring rotational channels. A central result of the present work is the successful application of the PINQC framework to extended rovibrational models containing larger rotational levels than those previously accessible in our conventional photoassociation calculations. The optimization remains numerically stable despite the increased complexity of the molecular system, demonstrating that differentiable optimization provides an effective strategy for treating rovibrational models of increased dimensionality. These results establish the PINQC framework as a promising computational tool for molecular photoassociation and motivate future investigations of increasingly complex rovibrational quantum-control problems.
Related papers
- Feedback-Controlled Magnon-Atom Entanglement and Photon Statistics [2.8834531620132817]
We introduce a magnon into a feedback-controlled quantum system.<n>We employ a Long Short-Term Memory network, a machine learning approach, to propagate the probability amplitudes to the steady state.
arXiv Detail & Related papers (2026-06-19T21:19:01Z) - Programming long-range interactions in analog quantum simulators [39.364243535886985]
Long-range interactions are the source of many equilibrium and out-of-equilibrium quantum many-body phenomena.<n>We develop a hybrid classical-quantum toolbox that exploits this tunability to enhance many-body state preparation in analog simulators.<n>Our results establish programmable long-range interactions as a powerful resource for next-generation analog quantum simulators.
arXiv Detail & Related papers (2026-04-24T12:06:38Z) - Digital Quantum Simulation of the Holstein-Primakoff Transformation on Noisy Qubits [40.8066152850216]
We study the digital quantum simulation of bosonic modes on a cloud-based superconducting quantum processor.<n>We examine the interplay between algorithmic and hardware-induced errors to identify optimal simulation parameters.
arXiv Detail & Related papers (2026-02-19T20:14:04Z) - Learning a Latent Pulse Shape Interface for Photoinjector Laser Systems [43.460344029773154]
Controlling the longitudinal laser pulse shape in photoinjectors of Free-Electron Lasers is a powerful lever for optimizing electron beam quality.<n>We present a generative modeling framework based on Wasserstein Autoencoders to learn a differentiable latent interface between pulse shaping and downstream beam dynamics.
arXiv Detail & Related papers (2026-02-19T11:09:33Z) - Hardware-inspired Continuous Variables Quantum Optical Neural Networks [0.27998963147546146]
In quantum optics, Gaussian operators induce affine mappings on the quadratures of optical modes.<n>This work presents a novel experimentally-feasible framework for continuous-variable quantum optical neural networks.
arXiv Detail & Related papers (2025-12-04T19:20:27Z) - HPC-Driven Modeling with ML-Based Surrogates for Magnon-Photon Dynamics in Hybrid Quantum Systems [31.546969452125214]
We present a massively parallel-based simulation framework for on-chip magnon-photon circuits.<n>Our framework enables scalable simulation and rapid prototyping of next-generation quantum and spintronic devices.
arXiv Detail & Related papers (2025-10-25T08:51:00Z) - Towards Quantum Enhanced Adversarial Robustness with Rydberg Reservoir Learning [45.92935470813908]
Quantum computing reservoir (QRC) leverages the high-dimensional, nonlinear dynamics inherent in quantum many-body systems.<n>Recent studies indicate that perturbation quantums based on variational circuits remain susceptible to adversarials.<n>We investigate the first systematic evaluation of adversarial robustness in a QR based learning model.
arXiv Detail & Related papers (2025-10-15T12:17:23Z) - Pulse-based optimization of quantum many-body states with Rydberg atoms in optical tweezer arrays [39.58317527488534]
We explore a pulse-based variational quantum eigensolver algorithm for Rydberg atoms in optical tweezer arrays.<n>We numerically demonstrate that the ground states of the one-dimensional antiferromagnetic Heisenberg model and the mixed-field Ising model can be accurately prepared.
arXiv Detail & Related papers (2025-07-25T10:51:49Z) - Enhancing Quantum Diffusion Models with Pairwise Bell State Entanglement [35.436358464279785]
This paper introduces a novel quantum diffusion model designed for Noisy Intermediate-Scale Quantum (NISQ) devices.
By leveraging quantum entanglement and superposition, this approach advances quantum generative learning.
arXiv Detail & Related papers (2024-11-24T20:14:57Z) - Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation [41.94295877935867]
We introduce a variational approach for fermionic time-dependent wave functions, surpassing mean-field approximations.
We use time-dependent Jastrow factors and backflow transformations, which are enhanced through neural networks parameterizations.
The results showcase the ability of our variational approach to accurately capture the time evolution, providing insight into the quantum dynamics of interacting electronic systems.
arXiv Detail & Related papers (2024-03-12T09:37:22Z) - Simulating the Mott transition on a noisy digital quantum computer via
Cartan-based fast-forwarding circuits [62.73367618671969]
Dynamical mean-field theory (DMFT) maps the local Green's function of the Hubbard model to that of the Anderson impurity model.
Quantum and hybrid quantum-classical algorithms have been proposed to efficiently solve impurity models.
This work presents the first computation of the Mott phase transition using noisy digital quantum hardware.
arXiv Detail & Related papers (2021-12-10T17:32:15Z) - Classical-to-quantum transition in multimode nonlinear systems with
strong photon-photon coupling [12.067269037074292]
We investigate the classical-to-quantum transition of such photonic nonlinear systems using the quantum cluster-expansion method.
This work presents a universal tool to study quantum dynamics of multimode systems and explore the nonlinear photonic devices for continuous-variable quantum information processing.
arXiv Detail & Related papers (2021-11-18T07:26:57Z) - Efficient simulation of ultrafast quantum nonlinear optics with matrix
product states [0.0]
We develop an algorithm to unravel the MPS quantum state into constituent temporal supermodes.
We observe the development of non-classical Wigner-function negativity in the solitonic mode and quantum corrections to the semiclassical dynamics of the pulse.
arXiv Detail & Related papers (2021-02-11T09:15:24Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.