Local privacy mechanisms preserve rate-double-robustness, enabling unbiased and semiparametrically efficient inference on target parameters indexed linearly by infinite-dimensional and nonlinearly by low-dimensional components from noisy private data.
Efficient error models for fault-tolerant architectures and the Pauli twirling approximation
13 Pith papers cite this work. Polarity classification is still indexing.
13
Pith papers citing it
abstract
The design and optimization of realistic architectures for fault-tolerant quantum computation requires error models that are both reliable and amenable to large-scale classical simulation. Perhaps the simplest and most practical general-purpose method for constructing such an error model is to twirl a given completely positive channel over the Pauli basis, a procedure we refer to as the Pauli twirling approximation (PTA). In this work we test the accuracy of the PTA for a small stabilizer measurement circuit relevant to fault-tolerant quantum computation, in the presence of both intrinsic gate errors and decoherence, and find excellent agreement over a wide range of physical error rates. The combined simplicity and accuracy of the PTA, along with its direct connection to the chi matrix of process tomography, suggests that it be used as a standard reference point for more refined error model constructions.
citation-role summary
method 2
background 1
citation-polarity summary
years
2026 13representative citing papers
Lindbladian perturbation theory reveals approximate symmetries on Pauli fidelities for Clifford gates, with only restricted off-diagonal dissipative errors breaking them at first order, enabling gauge fixing for SPAM identification.
Two detectors achieve near-perfect accuracy detecting PANDA-style adversarial attacks on autoencoder NIDS using image-space error localization and packet-feature consistency checks on IoT traffic.
QMCtwin simulates master-equation syndrome statistics for a distance-7 surface code and reveals biases and correlations absent in Pauli-twirled models.
ScoreStop introduces a functional score test for early stopping in gradient boosting, testing the null that the current predictor minimizes population risk with a scale-invariant statistic of known asymptotic distribution.
PUICL is a transformer pretrained on synthetic PU data from structural causal models that solves positive-unlabeled classification via in-context learning without gradient updates or fitting.
A curvature-aware spectral framework using the Laplace-Beltrami operator detects demographic biases in 3D face reconstruction that Euclidean metrics miss, validated by a user study showing 73.6% perceptual accuracy.
Derives augmented IPW estimators for occupation probabilities in coarsened multistate processes under coarsening at random, allowing time-varying confounders.
A one-step outcome imputation estimator is introduced as an alternative to multiple imputation for RCTs with missing data, constructing an efficient estimator via the influence function to achieve asymptotically valid inference.
Error-mitigated IBM quantum hardware reproduces extrapolated classical simulations of entanglement growth and local thermalization for a truncated SU(2) gauge theory on chains up to 101 plaquettes.
FTPrimitiveBench is a new benchmark suite for testing surface-code logical primitives under Pauli-biased, measurement-biased, and spatially non-uniform noise models, revealing that noise structure interacts distinctly with each primitive and decoder.
Develops a perturbative analytic framework extending ZPG to derive closed-form solutions for process matrices and Pauli error weights in photon-heralded gates between non-interacting emitters.
The clone-censor-weight approach is formalized and tested via simulations before application to a breast cancer cohort comparing 2 versus 5 years of adjuvant tamoxifen, yielding estimates with substantial uncertainty.
citing papers explorer
-
Private Rate-Double-Robust Inference
Local privacy mechanisms preserve rate-double-robustness, enabling unbiased and semiparametrically efficient inference on target parameters indexed linearly by infinite-dimensional and nonlinearly by low-dimensional components from noisy private data.
-
Symmetries of Pauli Noise from Lindbladian Dynamics
Lindbladian perturbation theory reveals approximate symmetries on Pauli fidelities for Clifford gates, with only restricted off-diagonal dissipative errors breaking them at first order, enabling gauge fixing for SPAM identification.
-
Detecting Adversarial Evasion Attacks Against Autoencoder-Based Network Intrusion Detection Systems
Two detectors achieve near-perfect accuracy detecting PANDA-style adversarial attacks on autoencoder NIDS using image-space error localization and packet-feature consistency checks on IoT traffic.
-
QMCtwin: Master-Equation Simulation of Syndrome Statistics Beyond Pauli Noise
QMCtwin simulates master-equation syndrome statistics for a distance-7 surface code and reveals biases and correlations absent in Pauli-twirled models.
-
ScoreStop: Gradient-based early stopping using functional score tests
ScoreStop introduces a functional score test for early stopping in gradient boosting, testing the null that the current predictor minimizes population risk with a scale-invariant statistic of known asymptotic distribution.
-
In-Context Positive-Unlabeled Learning
PUICL is a transformer pretrained on synthetic PU data from structural causal models that solves positive-unlabeled classification via in-context learning without gradient updates or fitting.
-
Discovering Geometric Biases in 3D Face Reconstruction: A Curvature-Aware Spectral Framework for Fairness Evaluation
A curvature-aware spectral framework using the Laplace-Beltrami operator detects demographic biases in 3D face reconstruction that Euclidean metrics miss, validated by a user study showing 73.6% perceptual accuracy.
-
Robust estimation of occupation probabilities for coarsened multistate processes
Derives augmented IPW estimators for occupation probabilities in coarsened multistate processes under coarsening at random, allowing time-varying confounders.
-
One-step Outcome Imputation: An Alternative to Multiple Imputation
A one-step outcome imputation estimator is introduced as an alternative to multiple imputation for RCTs with missing data, constructing an efficient estimator via the influence function to achieve asymptotically valid inference.
-
Local Thermalization of SU(2) Lattice Gauge Fields on Quantum Computers
Error-mitigated IBM quantum hardware reproduces extrapolated classical simulations of entanglement growth and local thermalization for a truncated SU(2) gauge theory on chains up to 101 plaquettes.
-
FTPrimitiveBench: A Benchmark Suite For Logical Computation Under Hardware-Motivated and Biased Noise Models
FTPrimitiveBench is a new benchmark suite for testing surface-code logical primitives under Pauli-biased, measurement-biased, and spatially non-uniform noise models, revealing that noise structure interacts distinctly with each primitive and decoder.
-
Characterization of errors in photon-heralded quantum operations between non-interacting quantum emitters
Develops a perturbative analytic framework extending ZPG to derive closed-form solutions for process matrices and Pauli error weights in photon-heralded gates between non-interacting emitters.
-
Estimating treatment duration effects via clone-censor-weight: a breast cancer case study
The clone-censor-weight approach is formalized and tested via simulations before application to a breast cancer cohort comparing 2 versus 5 years of adjuvant tamoxifen, yielding estimates with substantial uncertainty.