arXiv subjects

Yves Bérubé-Lauzière

Publications and source records attributed to Yves Bérubé-Lauzière.

12 recordsLinked to original sources

arXiv2026

Quantum-Assisted Optimization Guided by Machine-Learned Risk Maps for Aerial Surveillance Routing

Analog quantum computing with neutral atom computers is rapidly evolving into a promising way to perform combinatorial optimization tasks at scale. As technology matures, exploring real use cases leveraging such unique information processors becomes warranted; one example is logistics management where vehicles are assigned routes to perform a given task. Autonomous aerial vehicles (drones) are increasingly used for surveillance over a given territory. In this paper, we propose an innovative framework integrating classical machine learning forecasts and quantum annealing to find the best combination of tours for a given surveillance criterion. The risk maps produced by machine learning are used to find possible surveillance tours, while a quantum-assisted heuristic chooses the best combination, producing a full surveillance plan. By modelling our decision problem for drone paths as a Team Orienteering Problem (TOP) with additional constraints, we construct a new heuristic using quantum annealing to find good solutions. We apply this framework to wildfire prevention, where finding tours most likely to detect a starting fire has clear benefits. We study the effect of larger quantum resources on heuristic performance and compare those results to the use of classical resources.

quant-ph↗

arXiv2026

Gate Synthesis in Dephasing-Limited Nitrogen-Vacancy Ensembles

Ensemble nitrogen-vacancy (NV) centers are widely used for quantum sensing and magnetometry, where performance depends on the accurate implementation of microwave pulse sequences. In these systems, inhomogeneous broadening and short coherence times limit reliable multi-pulse control, while hardware imperfections and off-resonant excitation distort implemented rotations, making direct calibration of arbitrary gates tedious. To address this, we implement a control framework with a ZXZXZ gate decomposition which uses fixed-angle, phase-parameterized pulses, enabling universal single-qubit control from a single calibrated $ π/2$ primitive ($X_{π/2}$) along with virtual Z operations. We compare a standard pulse with a composite pulse designed for high-power operation in a regime where the Rabi frequency is comparable to the hyperfine splitting, leading to non-uniform evolution across hyperfine levels. Using pre-determined combinations of $π/2$ pulse sequences, we observe that standard pulses rapidly deviate from ideal behavior under repeated application, while the composite pulse suppresses this error accumulation by more than 70$\%$ for longer sequences despite its longer duration. In contrast, randomized benchmarking yields similar decay factors for both implementations, highlighting its limited sensitivity to coherent control errors. These results establish a practical route to robust control in short-coherence ensemble systems and emphasize the importance of pulse-level characterization.

quant-ph↗

arXiv2026

Zero bias field selective transition adressing of the NV center via pulse shaping

Nitrogen-vacancy (NV) centers in diamond are a leading platform for vector magnetometry, offering intrinsic sensitivity to both the magnitude and direction of magnetic fields. NV magnetometers typically rely on an external bias field to lift the degeneracy of the ground-state spin sublevels, enabling spectral discrimination of different NV orientations and spin transitions. At high accuracy, however, such a bias field systematically introduces errors through thermal, mechanical, and hysteretic drifts, thus hindering the accurate measurement of the magnetic field of interest. Several strategies have been proposed to address this limitation, including optical polarization-based orientation labeling, optical anisotropy, strong coupling to nearby nuclear spins, circular microwave polarization, and tailored pulse sequences. In this work, we introduce an optimization-based pulse-shaping control framework that enables selective and robust manipulation of NV ensembles without relying on a static bias field. Our method achieves both orientation-selective and subspace-selective control through optimal temporal modulation of the driving fields, providing a route to resolving spectral overlaps in degenerate NV systems.

quant-ph↗

arXiv2026

Quantum-enhanced Monte Carlo Tree Search framework for combinatorial optimization problems

Over the past decades, the operations research community has developed numerous effective optimization algorithms, yet quantum computing is emerging as a new computational paradigm with the potential to approach optimization problems more efficiently. Grover's algorithm offers a provable speedup for combinatorial optimization, but its circuit depth places it beyond current noisy intermediate-scale quantum (NISQ) devices. A more accessible alternative is to reformulate the optimization problem as a quadratic unconstrained binary optimization (QUBO) problem and apply quantum annealing; however, practical problem instances remain out of reach for existing hardware. We introduce AtomTreeSearch, a hybrid classical-quantum algorithm that integrates a quantum subroutine natively implementable on neutral-atom quantum computers within a Monte Carlo Tree Search framework. At each expansion step, a maximal weighted independent set of candidate actions provided by the quantum processor is selected, and these collective actions are performed to obtain a child node. We benchmark our method on the Traveling Salesman Problem, with instances of up to 60 cities on random Euclidean instances and up to 100 cities on TSPLIB instances. Our hybrid algorithm generally matches or outperforms both OR-Tools and simulated annealing on these instances, and we find that the quantum subroutine produces more diverse and higher-quality branches compared to classical alternate subroutines. These results suggest that carefully scoped quantum subroutines embedded in classical search frameworks represent a promising path toward near-term quantum utility in combinatorial optimization.

quant-ph↗

arXiv2026

Iterative Optimization with Partial Convergence Guarantees on Neutral Atom Quantum Computers

Neutral atom quantum computers (NAQCs) have emerged as a promising platform for solving the maximum weighted independent set (MWIS) problem. However, analog quantum approaches face two key limitations: constraints of the atomic layout on realizable graph geometries and the absence of performance guarantees. We introduce Lp-Quts, a hybrid quantum-classical framework that integrates an NAQC sampler into a classical cutting-plane algorithm. At each iteration, a relaxed linear program (RLP) bounds the MWIS and induces a reduced graph from which independent sets are sampled using an analog quantum sampler. A novel sample-informed separation problem guides odd-cycle cut selection and accelerates convergence. For t-perfect graphs, Lp-Quts inherits polynomial-time convergence guarantees from the classical theory of cutting planes. We evaluate our approach on instances with up to 300 vertices -- a scale that exceeds the capabilities of current NAQC hardware. In this regime, Lp-Quts reaches solutions within 5--10\% of optimality, outperforming direct analog quantum protocols and greedy baselines under equal sampling budgets. As expected, simulated annealing remains the strongest sample-based solver at this scale. These results demonstrate how quantum samplers can be effectively embedded within classical optimization frameworks to deliver near-optimal solutions with reduced quantum resources while preserving formal guarantees.

quant-ph↗

arXiv2026

Leveraging Analog Neutral Atom Quantum Computers for Diversified Pricing in Hybrid Column Generation Frameworks

In this work, we develop new pulse designs and embedding strategies to improve the analog quantum subroutines of hybrid column generation (CG) algorithms based on neutral-atoms quantum computers (NAQCs). These strategies are designed to improve the quality and diversity of the samples generated. We apply these to an important combinatorial optimization (CO) problem in logistics, namely the fleet assignment. Depending on the instance tested, our quantum protocol has a performance that is either comparable or worse than the best classical method tested, both in terms of the number of iterations and final objective value. We identify the cause of these suboptimal solutions as a result of our quantum protocol often generating high-quality but degenerate samples. We address this limitation by introducing a greedy post-processing technique, Make\_Diff, which applies bit-wise modifications to degenerate samples in order to return a non-degenerate set. With this modification, our quantum protocol becomes competitive with an exact solver for the subproblem, all the while being resilient to state preparation and measurements (SPAM) errors. We also compare our CG scheme with a Gurobi solver and find that it performs better on over 50\% of our synthetic instances and that, despite Gurobi having a more extensive runtime. These improvements and benchmarks herald the potential of deploying hybrid CG schemes on NISQ devices for industrially relevant CO problems.

quant-ph↗

arXiv2026

Triple-Tone Microwave Control for Sensitivity Optimization in Compact Ensemble Nitrogen-Vacancy Magnetometers

Ensembles of nitrogen-vacancy (NV) centers in diamond are a well-established platform for quantum magnetometry under ambient conditions. One challenge arises from the hyperfine structure of the NV, which, for the common $^{14}$N isotope, results in a threefold reduction of contrast and thus sensitivity. By addressing each of the NV hyperfine transitions individually, triple-tone microwave (MW) control can mitigate this sensitivity loss. Here, we experimentally and theoretically investigate the regimes in which triple-tone excitation offers an advantage over standard single-tone MW control for two DC magnetometry protocols: pulsed optically detected magnetic resonance (ODMR) and Ramsey interferometry. We validate a master equation model of the NV dynamics against ensemble NV measurements, and use the model to explore triple-tone vs single-tone sensitivity for different MW powers and NV dephasing rates. For pulsed ODMR, triple-tone driving improves sensitivity by up to a factor of three in the low-dephasing regime, with diminishing gains when dephasing rates approach the hyperfine splitting. In contrast, for Ramsey interferometry, triple-tone excitation only improves sensitivity if MW power is limited. Our results delineate the operating regimes where triple-tone control provides a practical strategy for enhancing NV ensemble magnetometry in portable and power-limited sensors.

quant-ph↗

arXiv2023

Time-of-Flight X-ray Measurements for Computed Tomography

Time-of-flight (ToF) measurements is a possible alternative to anti-scatter grids in computed tomography (CT). Simulations have shown a possible 75% reduction in the detrimental scattering contribution with a 100 ps FWHM timing resolution. A test bench comprising a pulsed X-ray source and a time-correlated detector has been designed to demonstrate the feasibility of time-of-flight measurements of X-rays using readout electronics inherited from a ToF-positron emission tomography project. A 86 ps FWHM coincidence time resolution have been achieved with 511 keV annihilation gamma-rays and a 155 ps FWHM timing jitter with a 120 kVp pulsed X-rays source.

physics.med-ph↗

arXiv2023

Automated Generation of Shuttling Sequences for a Linear Segmented Ion Trap Quantum Computer

A promising approach for scaling-up trapped-ion quantum computer platforms is by storing multiple trapped-ion qubit sets ('ion crystals') in segmented microchip traps and to interconnect these via physical movement of the ions ('shuttling'). Already for realizing quantum circuits with moderate complexity, the design of suitable qubit assignments and shuttling schedules require automation. Here, we describe and test algorithms which address exactly these tasks. We describe an algorithm for fully automated generation of shuttling schedules, complying to constraints imposed by a given trap structure. Furthermore, we introduce different methods for initial qubit assignment and compare these for random circuit (of up to 20 qubits) and quantum Fourier transform-like circuits, and generalized Toffoli gates of up to 40 qubits each. We find that for quantum circuits which contain a fixed structure, advanced assignment algorithms can serve to reduce the shuttling overhead.

quant-ph↗

arXiv2023

Preparation of cavity Fock state superpositions by reinforcement learning exploiting measurement back-action

Preparation of bosonic and general cavity quantum states usually relies on using open-loop control to reach a desired target state. In this work, a measurement-based feedback approach is used instead, exploiting the non-linearity of weak measurements alongside a coherent drive to prepare these states. The extension of previous work on Lyapunov-based control is shown to fail for this task. This prompts for a different approach, and reinforcement learning (RL) is resorted to here for this purpose. With such an approach, cavity eigenstate superpositions can be prepared with fidelities over 98$\%$ using only the measurements back-action as the non-linearity, while naturally incorporating detection of cavity photon jumps. Two different RL frameworks are analyzed: an off-policy approach recently introduced called truncated quantile critic~(TQC) and the on-policy method commonly used in quantum control, namely proximal policy optimization~(PPO). It is shown that TQC performs better at reaching higher target state fidelity preparation.

quant-ph↗

arXiv2022

State Initialization of a Hot Spin Qubit in a Double Quantum Dot by Measurement-Based Quantum Feedback Control

A measurement-based quantum feedback protocol is developed for spin state initialization in a gate-defined double quantum dot spin qubit coupled to a superconducting resonator. The protocol improves qubit state initialization as it is able to robustly prepare the spin in shorter time and reach a higher fidelity, which can be pre-set. Being able to pre-set the fidelity aimed at is a highly desired feature enabling qubit initialization to be more deterministic. The protocol developed herein is also effective at high temperatures, which is critical for the current efforts towards scaling up the number of qubits in quantum computers.

cond-mat.mes-hall↗

arXiv2022

Optimal Control of the Operating Regime of a Single Electron Double Quantum Dot

The double quantum dot device benefits from the advantages of both the spin and charge qubits, while offering ways to mitigate their drawbacks. Careful gate voltage modulation can grant greater spinlike or chargelike dynamics to the device, yielding long coherence times with the former and high electrical susceptibility with the latter for electrically driven spin rotations or coherent interactions with microwave photons. We show that optimal control pulses generated using the GRadient Ascent Pulse Engineering (GRAPE) algorithm can yield higher-fidelity operating regime transfers than can be achieved using linear methods.

cond-mat.mes-hall↗