Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 2511.17278

Enhancing Infrared Laser Dissociation of Molecules with the Electromagnetic Vacuum

Johan F. Triana·Felipe Herrera
View original source ↗Read source document ↗Export metadata ↓

Abstract

Controlling bond breaking is a long-standing goal in molecular physics. Infrared nanocavities are currently being developed for reaching exotic coupling regimes of cavity QED with a few molecules, but it is not well understood how chemical reactions would proceed in such systems. To address this, we study infrared laser photodissociation of a single CS$_{2}$ molecule with a stretching mode that strongly interacts with a resonant infrared vacuum, subject to a strong laser field that either resonantly drives the molecule at its fundamental vibration frequency or injects photons at the cavity resonance. We show that the intensities required for photodissociation are significantly lower inside the cavity than in free space, with a strong dependence on the type of driving condition. By directly injecting photons into the cavity, the molecule dissociates with two orders of magnitude less laser energy than by directly driving the vibrational mode. This photodissociation enhancement is a purely quantum mechanical effect that cannot be captured semi-classically. The intracavity ladder climbing dynamics is substantially modified relative to free space due to vacuum-induced admixing a large number of vibrational quantum numbers and the cavity field acting as a surrogate molecular mode that strongly interacts with the dissociative vibrational motion. Our work provides fundamental mechanistic understanding of chemical dynamics that can be used for designing new types of nanophotonics experiments that probe single-molecule chemistry.

Explore related subjects

quant-phphysics.chem-ph

Keep this discovery

BibTeXRIS

Johan F. Triana, Felipe Herrera. 2025-11-21. Enhancing Infrared Laser Dissociation of Molecules with the Electromagnetic Vacuum. https://arxiv.org/abs/2511.17278

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

KEEP EXPLORING

Related papers

arXiv2026

Probing the Error-Mitigation Threshold with Matrix Product States

Quantum error mitigation relies on accurate noise characterization, but mismatches between the actual and characterized noise can be amplified and drive a sharp threshold between successful and failed mitigation. In random circuits, this threshold maps onto a random-field Ising transition, but previous exact numerics were limited to small one-dimensional and all-to-all systems, leaving explicit two-dimensional architectures unresolved. We develop a fixed-bond-dimension matrix-product-state method for the replicated transfer dynamics that extends threshold calculations beyond exact propagation while retaining the finite-size signatures of the transition. At system sizes beyond previous exact studies, we recover the predicted absence of a threshold for quenched disorder in 1D, obtain a sharper annealed all-to-all critical point, and resolve architecture-dependent finite-depth thresholds in 2D square and heavy-hex circuits. These results establish replicated tensor-network dynamics as a practical tool for probing error-mitigation thresholds in large and higher-dimensional noisy circuits.

quant-ph↗
arXiv2026

Low-cost algorithm-to-execution framework for surface-code quantum computing

The execution of useful quantum algorithms on fault-tolerant processors requires more than a mapping from logical gates to encoded operations: the spatial organization, non-Clifford resource supply, and execution schedule must also be determined while keeping physical overhead within practical limits. Although the theoretical hierarchy from logical circuits to fault-tolerant operations is well established, these implementation choices are often specified and optimized separately. Here we develop a low-cost algorithm-to-execution framework for surface-code quantum computing. From hierarchical algorithm descriptions, it constructs dependency-preserving logical schedules and an executable workload capturing logical interactions, operation parallelism, and time-resolved non-Clifford demand, thereby linking logical computation to surface-code organization, resource-state preparation, and fault-tolerant execution in a traceable workflow. We apply the framework to twenty benchmark circuits across seven algorithm families and a hierarchically composed application-scale elliptic-curve discrete-logarithm workload. Physical costs vary substantially even for circuits with similar logical resource counts. Under our direct-rotation calibration, non-Clifford implementation selection reduces space-time volume by up to 241.5 times versus an all-synthesis baseline for the QAOA amplitude-amplification workload. Circuit-specific surface-code layouts reduce routed-latency estimates for all twenty benchmarks; thirteen also reduce space-time volume because communication savings outweigh added spatial overhead. These results show that low-cost fault-tolerant execution depends on computation scheduling and organization, not aggregate logical resource counts alone.

quant-ph↗
arXiv2026

Sample-optimal learning of stabilizer states

It is well-known that learning a pure $n$-qubit stabilizer state $|\psi\rangle$ both requires, and can be accomplished with, access to a number of copies of $|\psi\rangle$ linear in $n$. However, the precise constant coefficient of this scaling does not appear to have been determined. Here we prove that $L_\delta(n)$, the smallest number of copies from which a quantum procedure can identify any stabilizer state with failure probability at most $0<\delta<1/8$, satisfies $n+\lceil\log_2(1/\delta)\rceil-3\leq L_\delta(n)\leq n+\left\lceil\log_2(1/\delta)\right\rceil+4$. We present a polynomial-time quantum learning algorithm that saturates this bound, achieving a constant factor improvement in sample-complexity over previously known approaches. As an immediate corollary, we obtain via the Choi-Jamiolkowski isomorphism an algorithm for learning an unknown $n$-qubit Clifford unitary from $2n+\left\lceil\log_2(1/\delta)\right\rceil+4$ queries, the $n$-dependence of which we show to be optimal. Our proof technique, which involves Fourier analysis on the abelian group $\mathbb{Z}_4^n \times \mathbb{F}_2^{n(n-1)/2}$, seems to be qualitatively different to previous approaches to stabilizer state learning, and may be of some independent interest; in particular, it admits natural generalisations to further problems in quantum learning theory.

quant-ph↗