1134 papers
This paper presents a noise-robust, quantum-classical hybrid algorithm using Liouvillian recursion to compute many-body Green's functions on near-term quantum hardware, which subsequently enables more accurate ground state energy estimation via the Galitskii-Migdal formula than direct Hamiltonian expectation values.
This paper theoretically demonstrates that a hybrid cavity magnomechanical system comprising two YIG spheres and a central membrane, influenced by the Barnett effect, can generate multiple transparency windows, tunable Fano resonances, and controllable slow/fast light transitions while achieving nonreciprocal absorption and group delay through photon-phonon-magnon interactions.
This paper introduces MQED-QD, an open-source package that integrates macroscopic quantum electrodynamics with classical electromagnetic solvers to simulate exciton dynamics in complex dielectric and plasmonic environments, demonstrating how silver nanorods enhance long-range interactions and exciton delocalization compared to planar geometries.
The paper proposes novel standalone belief propagation decoders that exchange messages on the decoding graph to achieve code capacity thresholds for surface codes under depolarizing noise, offering a scalable, hardware-accelerated alternative to minimum weight perfect matching decoders.
This paper introduces "SpiderCat," a scalable method that derives formal lower bounds on CNOT gates for fault-tolerant CAT state preparation and provides explicit, optimal circuit constructions for a wide range of qubit counts and error thresholds by mapping the problem to characterizing specific 3-regular graphs.
This paper extends first-principles spin-lattice relaxation theory to include three-phonon processes, demonstrating that while these contributions are negligible for the studied Chromium nitride complex under experimental conditions—thereby validating the weak coupling assumption—the framework reveals that slightly stronger coupling could make three-phonon effects significant at room temperature.
This paper introduces clustered-cyclic quantum LDPC codes and a parallel product surgery protocol that enable highly parallel, fault-tolerant logical operations, including arbitrary parallel CNOTs, by leveraging directly addressable logical bases and engineered product-connection structures.
This paper introduces a graph-matching decoding framework for general two-dimensional topological translationally-invariant codes that coarse-grains syndromes into effective toric code excitations, proving it corrects errors up to a constant fraction of the code distance and achieves non-zero thresholds while demonstrating performance comparable to state-of-the-art decoders for bivariate bicycle codes.
This paper proposes a recursive implementation of 15-to-1 magic state distillation using lattice surgery on the surface code to reduce resource overhead for preparing and states, while noting that achieving output error rates comparable to the logical code requires a physical error threshold significantly lower than that of the underlying surface code.
This paper proposes and demonstrates a real-time feedback control framework that uses a proportional controller to adaptively shape simple laser fields, enabling diverse quantum systems to mimic target dynamics without prior waveform design.
This paper establishes a rigorous theoretical foundation for using single-qubit reference sequences in cross-entropy benchmarking by deriving a refined analytical expression that corrects systematic overestimations, thereby enabling reliable and high-precision characterization of multi-qubit entangling gates on superconducting quantum processors.
The paper introduces the "worm decoder," a Markov-Chain Monte-Carlo-based algorithm that achieves optimal decoding for various qLDPC codes by approximating logical error probabilities, offering rigorous efficiency guarantees for typical errors and demonstrating superior performance over existing methods even under depolarizing noise through the use of soft information.
This paper proposes a constant-depth magic state cultivation protocol for color codes that utilizes gauging to perform logical measurements, achieving high logical error rates with reduced circuit depth compared to previous methods, albeit at the cost of scalability due to the reliance on post-selection rather than full error correction.
This paper introduces Extreme Quantum Cognition Machines, a noise-tolerant quantum learning architecture that combines fixed quantum dynamics with a dynamical attention mechanism to perform deliberative decision-making, validated on linguistic tasks and applicable to fields like cybersecurity and biology.
This paper numerically demonstrates that weak measurements on the ground state of a one-dimensional spin system near a deconfined quantum critical point induce an asymmetric restructuring of entanglement across the phase boundary, suggesting the emergence of a weak first-order phase transition in the thermodynamic limit.
This paper demonstrates that simple local measurement strategies, specifically the greedy approach, are provably optimal for computing global Boolean properties of quantum sequences if and only if the target function is affine, while also guaranteeing a universal performance bound that remains competitive with unrestricted global measurements even under severe memory constraints.
This paper presents a heuristic algorithm for qubit mapping and shuttling sequence optimization in linear segmented trapped-ion quantum computers, demonstrating that it reduces the number of required ion displacements—which scale polynomially with qubit count—and that utilizing multiple interaction zones further minimizes qubit reordering overhead.
This paper introduces Spatiotemporal Pauli Processes (SPPs), a scalable framework that maps arbitrary non-Markovian quantum dynamics to efficient multi-time Pauli trajectories via process-separable combs, enabling the diagnosis and simulation of correlated noise that can cause catastrophic breakdowns in quantum error correction thresholds.
This paper proposes a novel low-depth amplitude estimation approach that reframes the problem as statistical eigengap estimation of an effective Hamiltonian, achieving state-of-the-art performance with simplified post-processing and optimal query-depth tradeoffs for early fault-tolerant applications.
This paper reports the first realization of a spin-resolved quantum-gas microscope for fermionic Sr, enabling site-resolved detection of all 10 spin states in SU(N) Fermi-Hubbard systems to probe exotic magnetism and magnetic correlations.