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We consider the problem of learning low-degree quantum objects up to $\varepsilon$-error in $\ell_2$-distance. We show the following results: $(i)$ unknown $n$-qubit degree-$d$ (in the Pauli basis) quantum channels and unitaries can be…

Learning about physical systems from quantum-enhanced experiments, relying on a quantum memory and quantum processing, can outperform learning from experiments in which only classical memory and processing are available. Whereas quantum…

Quantum Physics · Physics 2024-06-21 Matthias C. Caro

Parameter estimation is of fundamental importance in areas from atomic spectroscopy and atomic clocks to gravitational wave detection. Entangled probes provide a significant precision gain over classical strategies in the absence of noise.…

Quantum Physics · Physics 2013-10-28 R. Chaves , J. B. Brask , M. Markiewicz , J. Kolodynski , A. Acin

We address the problem of discriminating with minimal error probability two given quantum operations. We show that the use of entangled input states generally improves the discrimination. For Pauli channels we provide a complete comparison…

Quantum Physics · Physics 2009-11-11 Massimiliano F. Sacchi

A quantum observable and a channel are considered compatible if they form parts of the same measurement device, otherwise they are incompatible. Constrains on compatibility between observables and channels can be quantified via relations…

Quantum Physics · Physics 2018-02-28 T. Heinosaari , D. Reitzner , T. Rybár , M. Ziman

To successfully perform quantum computations, it is often necessary to first accurately characterize the noise in the underlying hardware. However, it is well known that fundamental limitations prevent the unique identification of the…

We present a classical algorithm based on Pauli propagation for estimating expectation values of arbitrary observables on random unstructured quantum circuits across all circuit architectures and depths, including those with all-to-all…

This paper considers a set of multiple independent control systems that are each connected over a non-stationary wireless channel. The goal is to maximize control performance over all the systems through the allocation of transmitting power…

Optimization and Control · Mathematics 2019-03-27 Mark Eisen , Konstantinos Gatsis , George J. Pappas , Alejandro Ribeiro

We study the problems of quantum tomography and shadow tomography using measurements performed on individual, identical copies of an unknown $d$-dimensional state. We first revisit a known lower bound due to Haah et al. (2017) on quantum…

Quantum Physics · Physics 2025-06-12 Angus Lowe , Ashwin Nayak

Quantum classification faces two key challenges. First, the difficulty of distinguishing between different classes varies: some class pairs are easy to separate, while others are more challenging. Second, practical execution is affected by…

Quantum Physics · Physics 2026-04-21 Yuhang Tu , Shengmei Zhao , Le Wang , Anqi Zhang

A striking feature of quantum error correcting codes is that they can sometimes be used to correct more errors than they can uniquely identify. Such degenerate codes have long been known, but have remained poorly understood. We provide a…

Quantum Physics · Physics 2007-05-23 Graeme Smith , John A. Smolin

Dual to the usual noisy channel coding problem, where a noisy (classical or quantum) channel is used to simulate a noiseless one, reverse Shannon theorems concern the use of noiseless channels to simulate noisy ones, and more generally the…

Quantum Physics · Physics 2014-07-22 Charles H. Bennett , Igor Devetak , Aram W. Harrow , Peter W. Shor , Andreas Winter

Analysis of quantum error correcting codes is typically done using a stochastic, Pauli channel error model for describing the noise on physical qubits. However, it was recently found that coherent errors (systematic rotations) on physical…

Quantum Physics · Physics 2018-01-09 Daniel Greenbaum , Zachary Dutton

We prove that learning an unknown quantum channel with input dimension $d_A$, output dimension $d_B$, and Choi rank $r$ to diamond distance $\varepsilon$ requires $ \Omega\!\left( \frac{d_A d_B r}{\varepsilon \log(d_B r / \varepsilon)}…

Quantum Physics · Physics 2026-01-21 Aadil Oufkir , Filippo Girardi

We derive new bounds on achievable precision in the most general adaptive quantum metrological scenarios. The bounds are proven to be asymptotically saturable and equivalent to the known parallel scheme bounds in the limit of large number…

We explore asymptotically optimal bounds for deviations of Bernoulli convolutions from the Poisson limit in terms of the Shannon relative entropy and the Pearson $\chi^2$-distance. The results are based on proper non-uniform estimates for…

Probability · Mathematics 2019-08-13 S. G. Bobkov , G. P. Chistyakov , F. Götze

Channel simulation algorithms can efficiently encode random samples from a prescribed target distribution $Q$ and find applications in machine learning-based lossy data compression. However, algorithms that encode exact samples usually have…

Information Theory · Computer Science 2024-05-16 Gergely Flamich , Lennie Wells

This paper focuses on error thresholds for Pauli channels. We numerically compute lower bounds for the thresholds using the analytic framework of coset weight enumerators pioneered by DiVincenzo, Shor and Smolin in 1998. In particular, we…

Quantum Physics · Physics 2026-03-05 Avantika Agarwal , Alan Bu , Amolak Ratan Kalra , Debbie Leung , Luke Schaeffer , Graeme Smith

We consider the asymptotic regularization of the maximal fidelity for the generalized Pauli channels, which is a problem similar to the classical channel capacity. In particular, we find the formulas for the extremal channel fidelities and…

Quantum Physics · Physics 2019-01-30 Katarzyna Siudzińska

Quantum error correction is instrumental in protecting quantum systems from noise in quantum computing and communication settings. Pauli channels can be efficiently simulated and threshold values for Pauli error rates under a variety of…

Quantum Physics · Physics 2017-04-25 Christopher Chamberland , Joel J. Wallman , Stefanie Beale , Raymond Laflamme