First digital quantum simulation of SU(2) matrix model real-time dynamics on Quantinuum H2 using Loschmidt echo, with systematic error breakdown and modest post-selection gains.
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Helios: A 98-qubit trapped-ion quantum computer
18 Pith papers cite this work. Polarity classification is still indexing.
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2026 18representative citing papers
Linearized gate set tomography scales error characterization to many qubits via sparse models, linear fitting, and shallow circuits, with simulations showing accuracy on 10-qubit systems including crosstalk.
Two constructions yield strong unitary k-designs and pseudorandom unitaries on D-dimensional grids with provably optimal depth.
Monte Carlo-assisted tightening of the energy-based boson truncation bound substantially reduces volume dependence in (1+1)D scalar field theory and (2+1)D U(1) gauge theory.
Dynamarq is a new scalable benchmarking framework that defines structural features for dynamic quantum circuits and uses statistical models to predict hardware fidelity with transferable parameters.
A qubit-reduction method for hypergraph product codes preserves dimension, distance, and fault-tolerance properties, producing smaller codes such as [[441,64,6]] from [[610,64,6]] with comparable noise performance and compatibility with logical gates.
Optimized QED intervals plus steady-state extraction enable PEC+QED to deliver 2-11x lower error than PEC alone on Iceberg codes for QAOA.
A trapped-ion architecture based on LDPC codes and cat-state factories achieves 110 logical qubits and one million T gates per day using 2514 physical qubits, with estimates for Heisenberg model simulation on 100 sites in one month using 10000 qubits.
SimpleTES scales test-time evaluation in LLMs to discover state-of-the-art solutions on 21 scientific problems across six domains, outperforming frontier models and optimization pipelines with examples like 2x faster LASSO and new Erdos constructions.
Singly-ionized yttrium (89Y+) is positioned as a trapped-ion qubit with nuclear-spin storage, metastable manifolds, and isolated transitions for initialization, readout, and gates.
Mixed physical-logical datasets for zero-noise extrapolation reduce estimator variance and physical runtime by orders of magnitude compared to pure logical or pure physical strategies when error correction suppresses noise by a factor of 0.1 or less.
Heterogeneous quantum architectures with task-specific hardware and QEC encodings deliver up to 138x lower physical-qubit overhead than monolithic baselines for fault-tolerant algorithms, including RSA-2048 factoring at 190k-381k qubits.
High motional frequency ion trapping reduces decoherence effects and accelerates experimental duty cycles in quantum information science.
Exascale classical simulation validates noise-tolerant performance of a 98-qubit QPU up to 48 qubits for LR-QAOA, with statistical analysis showing coherent regime up to 93 qubits before outputs become indistinguishable from random.
Sparse qubit connectivity raises compiled depth in noisy IQP circuits, requiring lower effective noise to remain outside the classically simulatable regime compared to fully connected layouts.
A framework with operational criteria and a trapped-atom hardware proposal for achieving statistically significant quantum advantage in latency-constrained nonlocal games.
The authors present Pilot-Quantum, a middleware for adaptive resource management in hybrid quantum-HPC systems, along with execution motifs and a performance modeling toolkit called Q-Dreamer.
Qudit encoding of the vibrational Hamiltonian yields the most accurate population transfer simulations for CO2 and H2O compared to binary and direct qubit encodings when entangling gate error rates are held equal.
citing papers explorer
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Simulating the dynamics of an SU(2) matrix model on a trapped-ion quantum computer
First digital quantum simulation of SU(2) matrix model real-time dynamics on Quantinuum H2 using Loschmidt echo, with systematic error breakdown and modest post-selection gains.
-
Runtime-efficient zero-noise extrapolation from mixed physical and logical data
Mixed physical-logical datasets for zero-noise extrapolation reduce estimator variance and physical runtime by orders of magnitude compared to pure logical or pure physical strategies when error correction suppresses noise by a factor of 0.1 or less.