arXiv subjects

Bruno Ximenez

Publications and source records attributed to Bruno Ximenez.

8 recordsLinked to original sources

arXiv2026

Exploring the Relaxation Landscape of a 2D Quantum Magnet on a 256-Qubit Processor

How quantum matter relaxes far from equilibrium is a central open problem in many-body physics, and one for which analog quantum simulators are well positioned to move from confirming theory to discovering new physics. Here, we use a two-dimensional Rydberg atom array of 256 qubits to map the relaxation landscape of the two-dimensional transverse-field Ising model across its phase diagram. Beyond the expected rapid thermalization, we identify two further regimes. The first is a prethermal regime whose dynamics are governed by an effective XY model. The second, and most unexpected, is a crossover regime characterized by a slowdown in relaxation. This slowdown occurs precisely where state-of-the-art classical tensor-network methods lose control at late times, whereas the quantum simulation remains consistent across system sizes. These results establish Rydberg atom arrays as a platform for scientific discovery in nonequilibrium quantum many-body dynamics.

quant-ph↗

arXiv2026

Defect-free arrays at the thousand-atom scale in a 4-K cryogenic environment

We report on a cryogenic platform at 4 K incorporating high numerical aperture optics for the generation of large-scale tweezers arrays, and compatible with Rydberg-state manipulation. We achieve trapping lifetimes of around 5000 s, significantly extending the available experimental time for the preparation of large-scale arrays. By combining two trapping lasers at different wavelengths and by minimizing other atom losses during the rearrangement and imaging processes, we demonstrate the preparation of defect-free arrays with up to 1024 atoms. Our cryogenic design opens exciting prospects for analog and digital quantum computing.

physics.atom-ph↗

arXiv2026

One-to-one quantum simulation of a frustrated magnet with 256 qubits

Analog quantum simulators offer a powerful microscopic probe of quantum many-body systems, yet have largely been benchmarked against model Hamiltonians rather than real materials. Here, we use a 256-qubit Rydberg simulator to implement the effective Hamiltonian of the frustrated triangular-lattice magnet TmMgGaO$_4$. Simulated magnetization curves agree quantitatively with susceptibility measurements on single crystals, and both platforms consistently determine the antiferromagnetic phase transition. Snapshot-resolved analysis confirms that quantum fluctuations, rather than disorder, govern the intermediate paramagnetic regime. Having established this correspondence, we access non-equilibrium dynamics following a sudden quench, a regime at picosecond material timescales where entanglement growth places the problem beyond classical reach. The simulator reveals thermalization of local observables, demonstrating that analog quantum simulation can reproduce and extend the physics of a real material.

quant-ph↗

arXiv2025

Resource assessment of classical and quantum hardware for post-quench dynamics

We estimate the run-time and energy consumption of simulating non-equilibrium dynamics on neutral atom quantum computers in analog mode, directly comparing their performance to state-of-the-art classical methods, namely Matrix Product States and Neural Quantum States. By collecting both experimental data from a quantum processing unit (QPU) in analog mode and numerical benchmarks, we enable accurate predictions of run-time and energy consumption for large-scale simulations on both QPUs and classical systems through fitting of theoretical scaling laws. Our analysis shows that neutral atom devices are already operating in a competitive regime, achieving comparable or superior performance to classical approaches while consuming significantly less energy. These results demonstrate the potential of analog neutral atom quantum computing for energy-efficient simulation and highlight a viable path toward sustainable computational strategies.

quant-ph↗

arXiv2024

Rearrangement of single atoms in a 2000-site optical tweezers array at cryogenic temperatures

We report on the trapping of single rubidium atoms in large arrays of optical tweezers comprising up to 2088 sites in a cryogenic environment at 6 K. Our approach relies on the use of microscope objectives that are in-vacuum but at room temperature, in combination with windowless thermal shields into which the objectives are protruding to ensure a cryogenic environment for the trapped atoms. To achieve enough optical power for efficient trapping, we combine two lasers at slightly different wavelengths. We discuss the performance and limitations of our design. Finally, we demonstrate atom-by-atom rearrangement of an 828-atom target array using moving optical tweezers controlled by a field-programmable gate array.

physics.atom-ph↗

arXiv2024

Graph Algorithms with Neutral Atom Quantum Processors

Neutral atom technology has steadily demonstrated significant theoretical and experimental advancements, positioning itself as a front-runner platform for running quantum algorithms. One unique advantage of this technology lies in the ability to reconfigure the geometry of the qubit register, from shot to shot. This unique feature makes possible the native embedding of graph-structured problems at the hardware level, with profound consequences for the resolution of complex optimization and machine learning tasks. By driving qubits, one can generate processed quantum states which retain graph complex properties. These states can then be leveraged to offer direct solutions to problems or as resources in hybrid quantum-classical schemes. In this paper, we review the advancements in quantum algorithms for graph problems running on neutral atom Quantum Processing Units (QPUs), and discuss recently introduced embedding and problem-solving techniques. In addition, we clarify ongoing advancements in hardware, with an emphasis on enhancing the scalability, controllability and computation repetition rate of neutral atom QPUs.

quant-ph↗

arXiv2022

Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor

Using a quantum processor to embed and process classical data enables the generation of correlations between variables that are inefficient to represent through classical computation. A fundamental question is whether these correlations could be harnessed to enhance learning performances on real datasets. Here, we report the use of a neutral atom quantum processor comprising up to $32$ qubits to implement machine learning tasks on graph-structured data. To that end, we introduce a quantum feature map to encode the information about graphs in the parameters of a tunable Hamiltonian acting on an array of qubits. Using this tool, we first show that interactions in the quantum system can be used to distinguish non-isomorphic graphs that are locally equivalent. We then realize a toxicity screening experiment, consisting of a binary classification protocol on a biochemistry dataset comprising $286$ molecules of sizes ranging from $2$ to $32$ nodes, and obtain results which are comparable to those using the best classical kernels. Using techniques to compare the geometry of the feature spaces associated with kernel methods, we then show evidence that the quantum feature map perceives data in an original way, which is hard to replicate using classical kernels.

quant-ph↗

arXiv2022

In-situ equalization of single-atom loading in large-scale optical tweezers arrays

We report on the realization of large assembled arrays of more than 300 single $^{87}$Rb atoms trapped in optical tweezers in a cryogenic environment at $\sim4$~K. For arrays with $N_{\rm a}=324$ atoms, the assembly process results in defect-free arrays in $\sim37\%$ of the realizations. To achieve this high assembling efficiency, we equalize the loading probability of the traps within the array using a closed-loop optimization of the power of each optical tweezers, based on the analysis of the fluorescence time-traces of atoms loaded in the traps.

physics.atom-ph↗