arXiv subjects

Victor Drouin-Touchette

Publications and source records attributed to Victor Drouin-Touchette.

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

Interaction-Aware Embedding Optimization for Neutral-Atom Quantum Processors

Neutral atom-based quantum computers have the ability to dynamically reshape the qubit register geometry between experimental runs. This capability enables different types of problems to be mapped directly onto the hardware, significantly enhancing the efficiency of solving, for instance, complex optimization and machine learning use-cases. However, this flexibility requires finding atom positions to implement target pairwise interactions, inducing a difficult nonconvex optimization for setting up the quantum machine. In this work, we introduce a new force-directed method that targets interactions to encode the input problem on the quantum computer. Numerical results show that our new method can improve embedding feasibility and solution quality by orders of magnitude, and remains reliable on the largest instances.

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

Concentration-Free Quantum Kernel Learning in the Rydberg Blockade

Quantum kernel methods (QKMs) offer an appealing framework for machine learning on near-term quantum computers. However, QKMs generically suffer from exponential concentration, requiring an exponential number of measurements to resolve kernel values, with the exception of trivial (i.e., classically simulable) kernels. Here we propose a QKM that is free of exponential concentration, yet remains hard to simulate classically. Our QKM utilizes the weak ergodicity-breaking many-body dynamics in the Rydberg blockade of coherently driven neutral atom arrays. We demonstrate the fundamental properties of our QKM by analytically solving an approximate toy model of its underpinning quantum dynamics, as well as by extensive numerical simulations on randomly generated datasets. We further show that the proposed kernel exhibits effective learning on real data. The proposed QKM can be implemented in current neutral atom quantum computers. Along the way, we uncover novel physical insights into the thermalization of weak ergodicity-breaking systems through the non-stabilizerness of the underlying Rydberg-blockaded dynamics, which directly governs the classical simulability of the proposed kernel.

cond-mat.str-el↗

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↗

arXiv2025

Quantum Counting in the Rydberg Blockade

We propose a quantum algorithm for approximately counting the number of solutions to planar 2-satisfiability (2SAT) formulas natively on neutral atom quantum computers. Our algorithm maps Boolean variables to atomic registers arranged in space according to a given formula, so that 2SAT constraints are enforced via the Rydberg blockade between neighboring atoms. A quench under Rydberg dynamics of an initial computational basis state produces a superposition of all solutions after a sufficiently long evolution. For almost uniform superpositions, a polynomial number of measurements is enough to estimate the solution count up to any constant multiplicative factor via sampling based counting. We demonstrate numerically that this protocol leads to almost uniform solution sampling in 1D and 2D grids and that it produces accurate counts for 2SAT instances on punctured grids, suggesting its general applicability as a heuristic for #P-complete problems.

quant-ph↗

arXiv2024

Simulating the Transverse Field Ising Model on the Kagome Lattice using a Programmable Quantum Annealer

The presence of competing interactions due to geometry leads to frustration in quantum spin models. As a consequence, the ground state of such systems often displays a large degeneracy that can be lifted due to thermal or quantum effects. One such example is the antiferromagnetic Ising model on the Kagome lattice. It was shown that while the same model on the triangular lattice is ordered at zero temperature for small transverse field due to an order by disorder mechanism, the Kagome lattice resists any such effects and exhibits only short range spin correlations and a trivial paramagnetic phase. We embed this model on the latest architecture of D-Wave's quantum annealer, the Advantage2 prototype, which uses the highly connected Zephyr graph. Using advanced embedding and calibration techniques, we are able to embed a Kagome lattice with mixed open and periodic boundary conditions of 231 sites on the full graph of the currently available prototype. Through forward annealing experiments, we show that under a finite longitudinal field the system exhibits a one-third magnetization plateau, consistent with a classical spin liquid state of reduced entropy. An anneal-pause-quench protocol is then used to extract an experimental ensemble of states resulting from the equilibration of the model at finite transverse and longitudinal field. This allows us to construct a partial phase diagram and confirm that the system exits the constrained Hilbert space of the classical spin liquid when subjected to a transverse field. We connect our results to previous theoretical results and quantum Monte Carlo simulation, which helps us confirm the validity of the quantum simulation realized here, thereby extracting insight into the performance of the D-Wave quantum annealer to simulate non-trivial quantum systems in equilibrium.

cond-mat.stat-mech↗

arXiv2022

Interplay of charge and spin fluctuations in a Hund's coupled impurity

In Hund's metals, the local ferromagnetic interaction between orbitals leads to an emergence of complex electronic states with large and slowly fluctuating magnetic moments. Introducing the Hund's coupled mixed valence quantum impurity, we gain analytic insight into recent numerical renormalization group studies. We show that valence fluctuations drastically impede the development of a large fluctuating moment over a wide range of temperatures and energy, characterized by quenched orbital degrees of freedom and a singular logarithmic behavior of the spin susceptibility $χ_{\rm sp}''(ω) \propto [ω\ln(ω/T_K^{\rm eff})^2]^{-1}$, closely resembling power-law scaling $χ_{\rm sp}''(ω) \sim ω^{-γ}$. Such singular spin fluctuations are suspected to play an important role in future models of Hund's driven Cooper pairing.

cond-mat.str-el↗

arXiv2022

The Kosterlitz-Thouless phase transition: an introduction for the intrepid student

This is a set of notes recalling some of the most important results on the XY model from the ground up. They are meant for a junior researcher wanting to get accustomed to the Kosterlitz-Thouless phase transition in the context of the 2D classical XY model. The connection to the 2D Coulomb gas is presented in detail, as well as the renormalization group flow obtained from this dual representation. A numerical Monte-Carlo approach to the classical XY model is presented. Finally, two physical setting that realize the celebrated Kosterlitz-Thouless phase transition are presented: superfluid and liquid crystal thin films.

cond-mat.stat-mech↗

arXiv2021

Emergent Potts Order in a Coupled Hexatic-Nematic XY model

Addressing the nature of an unexpected smectic-A' phase in liquid crystal 54COOBC films, we perform large scale Monte Carlo simulations of a coupled hexatic-nematic XY model. The resulting finite-temperature phase diagram reveals a small region with composite Potts $\mathbb{Z}_3$ order above the vortex binding transition; this phase is characterized by relative hexatic-nematic ordering though both variables are disordered. The system develops algebraic hexatic and nematic order only at a lower temperature. This multi-step melting scenario agrees well with the experimental observations of a sharp specific heat anomaly that emerges above the onset of hexatic positional order. We therefore propose that the smectic-A' phase is characterized by composite Potts order and bound-states of fractional vortices.

cond-mat.stat-mech↗

arXiv2021

Emergent moments in a Hund's impurity

Motivated by the relevance of Hund's coupling in the context of multiorbital superconductors, we revisit the problem of a multiorbital Kondo impurity with Hund's interaction. Using dynamical large-N techniques, we propose an efficient approach that retains the essential physics at play, while providing a pathway to scalable quantum impurity solvers. We are able to follow the ground state, dynamic, and thermodynamic properties of this system over many decades of temperature. Our approach captures the emergence of large moments, and follows the stretched evolution of the physics down to their exponentially suppressed Kondo temperature. We focus our analysis on the intermediate finite temperature phase which presents an alternate paramagnetic state due to the emergent moment, and discuss the relevance of this regime to Hund's metals.

cond-mat.str-el↗