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.
Evaluating the performance of quantum processing units at large width and depth
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 4
citation-polarity summary
fields
quant-ph 5years
2026 5roles
background 4representative citing papers
First digital quantum simulation of an SU(2) bosonic matrix model on Quantinuum H2, with Loschmidt-echo dynamics and a three-way error budget showing post-selection and ZNE give only modest, non-scaling gains.
A regularized Pauli-sparse counterdiabatic method is added to linear-ramp QAOA, yielding higher approximation ratios on ferromagnetic chain and perturbed MaxCut instances than the uncorrected ramp.
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.
A review summarizing superconducting qubit types, DiVincenzo criteria implementations, coherence limits from defects, and large-scale integration strategies for quantum computing.
citing papers explorer
-
Characterizing and Benchmarking Dynamic Quantum Circuits
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.
-
Simulating the dynamics of an SU(2) matrix model on a trapped-ion quantum computer
First digital quantum simulation of an SU(2) bosonic matrix model on Quantinuum H2, with Loschmidt-echo dynamics and a three-way error budget showing post-selection and ZNE give only modest, non-scaling gains.
-
Pauli-Sparse regularised Counterdiabatic Shortcuts for Linear-Ramp QAOA
A regularized Pauli-sparse counterdiabatic method is added to linear-ramp QAOA, yielding higher approximation ratios on ferromagnetic chain and perturbed MaxCut instances than the uncorrected ramp.
-
Large-Scale Quantum Circuit Simulation on an Exascale System for QPU Benchmarking
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.
-
Review of Superconducting Qubit Devices and Their Large-Scale Integration
A review summarizing superconducting qubit types, DiVincenzo criteria implementations, coherence limits from defects, and large-scale integration strategies for quantum computing.