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Tradeoffs between the information rate and fidelity of quantum error-correcting codes are discussed. Quantum channels to be considered are those subject to independent errors and modeled as tensor products of copies of a general completely…

Quantum Physics · Physics 2016-11-18 Mitsuru Hamada

The Quantum Reverse Shannon Theorem has been a milestone in quantum information theory. It states that asymptotically reliable simulation of a quantum channel, assisted by unlimited shared entanglement, requires a rate of classical…

Quantum Physics · Physics 2025-02-18 Ke Li , Yongsheng Yao

It is well known that exact notions of model abstraction and reduction for dynamical systems may not be robust enough in practice because they are highly sensitive to the specific choice of parameters. In this paper we consider this problem…

Systems and Control · Computer Science 2018-07-19 Luca Cardelli , Mirco Tribastone , Max Tschaikowski , Andrea Vandin

We consider a type of nonnormal approximation of infinitely divisible distributions that incorporates compound Poisson, Gamma, and normal distributions. The approximation relies on achieving higher orders of cumulant matching, to obtain…

Probability · Mathematics 2013-04-24 Zhiyi Chi

We consider the random regular $k$-NAE-SAT problem with $n$ variables each appearing in exactly $d$ clauses. For all $k$ exceeding an absolute constant $k_0$, we establish explicitly the satisfiability threshold $d_*=d_*(k)$. We prove that…

Probability · Mathematics 2013-10-18 Jian Ding , Allan Sly , Nike Sun

We consider energy-constrained infinite-dimensional quantum channels from a given system (satisfying a certain condition) to any other systems. We show that dealing with basic capacities of these channels we may assume (accepting…

Quantum Physics · Physics 2021-09-28 M. E. Shirokov

Variance-Gamma distributions are widely used in financial modelling and contain as special cases the normal, Gamma and Laplace distributions. In this paper we extend Stein's method to this class of distributions. In particular, we obtain a…

Probability · Mathematics 2014-04-01 Robert E. Gaunt

For $D$ a bounded domain in $\mathbb R^d, d \ge 2,$ with smooth boundary $\partial D$, the non-linear inverse problem of recovering the unknown conductivity $\gamma$ determining solutions $u=u_{\gamma, f}$ of the partial differential…

Statistics Theory · Mathematics 2020-04-21 Kweku Abraham , Richard Nickl

Protocols for discriminating between a pair of channels or for estimating a channel parameter can often be aided by adaptivity or by entanglement between the probe states. This can make it difficult to bound the best possible performance…

Quantum Physics · Physics 2021-10-07 Jason L. Pereira , Leonardo Banchi , Stefano Pirandola

There is currently a significant need for robust and efficient methods for characterizing quantum devices. While there has been significant progress in this direction, there remains a crucial need to precisely determine the strength and…

Quantum Physics · Physics 2019-09-04 Arnaud Carignan-Dugas , Joel J. Wallman , Joseph Emerson

Channel capacity describes the size of the nearly ideal channels, which can be obtained from many uses of a given channel, using an optimal error correcting code. In this paper we collect and compare minor and major variations in the…

Quantum Physics · Physics 2009-11-10 Dennis Kretschmann , Reinhard F Werner

The generation of certifiable randomness is the most fundamental information-theoretic task that meaningfully separates quantum devices from their classical counterparts. We propose a protocol for exponential certified randomness expansion…

Quantum Physics · Physics 2019-01-14 Matthew Coudron , Jalex Stark , Thomas Vidick

A quantum channel is sufficient with respect to a set of input states if it can be reversed on this set. In the approximate version, the input states can be recovered within an error bounded by the decrease of the relative entropy under the…

Quantum Physics · Physics 2024-11-14 Anna Jenčová

This paper provides new error bounds on "consistent" reconstruction methods for signals observed from quantized random projections. Those signal estimation techniques guarantee a perfect matching between the available quantized data and a…

Information Theory · Computer Science 2016-04-21 Laurent Jacques

A fundamental question in systems biology is what combinations of mean and variance of the species present in a stochastic biochemical reaction network are attainable by perturbing the system with an external signal. To address this…

Systems and Control · Computer Science 2017-05-02 Francesca Parise , Maria Elena Valcher , John Lygeros

This paper introduces a new and ubiquitous framework for establishing achievability results in \emph{network information theory} (NIT) problems. The framework uses random binning arguments and is based on a duality between channel and…

Information Theory · Computer Science 2014-08-25 Mohammad Hossein Yassaee , Mohammad Reza Aref , Amin Gohari

In this paper, we propose a method to approximate the Gaussian function on ${\mathbb R}$ by a short cosine sum. We generalise and extend the differential approximation method proposed in [4, 40] to approximate $\mathrm{e}^{-t^{2}/2\sigma}$…

Numerical Analysis · Mathematics 2025-05-23 Nadiia Derevianko , Gerlind Plonka

We derive a universal performance limit for coherent quantum control in the presence of modeled and unmodeled uncertainties. For any target unitary $W$ that is implementable in the absence of error, we prove that the worst-case (and hence…

Quantum Physics · Physics 2025-07-14 Robert L. Kosut , Daniel A. Lidar , Herschel Rabitz

The number of random bits required to approximate a target distribution in terms of un-normalized informational divergence is considered. It is shown that for a variable-to-variable length encoder, this number is lower bounded by the…

Information Theory · Computer Science 2013-08-02 Georg Böcherer , Rana Ali Amjad

This paper investigates the approximation of Gaussian random variables in Banach spaces, focusing on the high-probability bounds for the approximation of Gaussian random variables using finitely many observations. We derive non-asymptotic…

Statistics Theory · Mathematics 2025-08-28 Daniel Winkle , Ingo Steinwart , Bernard Haasdonk
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