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One of the challenging scientific computing problems is topology optimization, where searching through the combinatorially complex configurations and solving the constraints of partial differential equations need to be done simultaneously.…

Quantum Physics · Physics 2025-03-05 Jungin E. Kim , Yan Wang

In this work we derive a second-order approach to bilevel optimization, a type of mathematical programming in which the solution to a parameterized optimization problem (the "lower" problem) is itself to be optimized (in the "upper"…

Optimization and Control · Mathematics 2022-05-06 Robert Dyro , Edward Schmerling , Nikos Arechiga , Marco Pavone

Network verification (NWV), broadly defined as the verification of properties of distributed protocols used in network systems, cannot be efficiently solved on classical hardware via brute force. Prior work has developed a variety of…

We develop a device-independent framework for testing quantum channels. That is, we falsify a hypothesis about a quantum channel based only on an observed set of input-output correlations. Formally, the problem consists of characterizing…

Quantum Physics · Physics 2017-03-17 Michele Dall'Arno , Sarah Brandsen , Francesco Buscemi

This work presents a differentiable geometric parameterization of quantum channels in Kraus representation, which can be efficiently probed to find an unknown quantum channel. We explore its feasibility in finding the quasi inverse…

Quantum Physics · Physics 2025-12-02 Zain Ateeq , Muhammad Faryad

Analytic continuation of numerical data obtained in imaginary time or frequency has become an essential part of many branches of quantum computational physics. It is, however, an ill-conditioned procedure and thus a hard numerical problem.…

Strongly Correlated Electrons · Physics 2016-08-18 Dominic Bergeron , A. -M. S. Tremblay

The ability to transfer coherent quantum information between systems is a fundamental component of quantum technologies and leads to coherent correlations within the global quantum process. However correlation structures in quantum channels…

Quantum Physics · Physics 2022-05-03 Matthew Girling , Cristina Cirstoiu , David Jennings

Gradient descent method, as one of the major methods in numerical optimization, is the key ingredient in many machine learning algorithms. As one of the most fundamental way to solve the optimization problems, it promises the function value…

Quantum Physics · Physics 2021-02-01 Keren Li , Shijie Wei , Feihao Zhang , Pan Gao , Zengrong Zhou , Tao Xin , Xiaoting Wang , Guilu Long

We present a nonintrusive method for reliably estimating the noise level during quantum computation and quantum communication protected by quantum error-correcting codes. As preprocessing of quantum error correction, our scheme estimates…

Quantum Physics · Physics 2014-05-27 Yuichiro Fujiwara

Variational quantum algorithms and, in particular, variants of the varational quantum eigensolver have been proposed to address combinatorial optimization (CO) problems. Using only shallow ansatz circuits, these approaches are deemed…

Quantum Physics · Physics 2026-04-14 Tim Schwägerl , Yahui Chai , Tobias Hartung , Karl Jansen , Stefan Kühn

Quantum channels generally reduce the distinguishability of quantum states, limiting information transmission and processing. Previous work introduced a protocol capable of increasing the distinguishability of states after the action of a…

Quantum Physics · Physics 2026-05-08 Gabriel M. Arantes , Barbara Amaral , Nadja K. Bernardes

State-of-the-art quantum computers can only reliably execute circuits with limited qubit numbers and computational depth. This severely reduces the scope of algorithms that can be run. While numerous techniques have been invented to exploit…

Quantum Physics · Physics 2023-12-25 Adrián Pérez-Salinas , Radoica Draškić , Jordi Tura , Vedran Dunjko

We develop a rigorous framework for quantifying quantum coherence in finite-dimensional systems by applying the Schur-Horn majorization theorem to relate eigenvalue distributions and diagonal entries of density matrices. Building on this…

Quantum Physics · Physics 2025-06-06 Tariq Aziz , Meng-Long Song , Liu Ye , Dong Wang

Semidefinite programs are convex optimisation problems involving a linear objective function and a domain of positive semidefinite matrices. Over the last two decades, they have become an indispensable tool in quantum information science.…

Quantum Physics · Physics 2024-12-17 Armin Tavakoli , Alejandro Pozas-Kerstjens , Peter Brown , Mateus Araújo

The group symmetries inherent in quantum channels often make them tractable and applicable to various problems in quantum information theory. In this paper, we introduce natural probability distributions for covariant quantum channels.…

Quantum Physics · Physics 2025-07-17 Ion Nechita , Sang-Jun Park

We construct a new entanglement-assisted quantum polar coding scheme which achieves the symmetric coherent information rate by synthesizing "amplitude" and "phase" channels from a given, arbitrary quantum channel. We first demonstrate the…

Quantum Physics · Physics 2012-09-04 Mark M. Wilde , Joseph M. Renes

We analyze quantum communication properties of phase-covariant channels depending on their degree of non-unitality. In particular, we derive analytical formulas for minimal and maximal channel fidelity on pure states and maximal output…

Quantum Physics · Physics 2023-05-03 Katarzyna Siudzińska , Michał Studziński

In classical information theory, the Doeblin coefficient of a classical channel provides an efficiently computable upper bound on the total-variation contraction coefficient of the channel, leading to what is known as a strong…

Quantum Physics · Physics 2026-05-27 Ian George , Christoph Hirche , Theshani Nuradha , Mark M. Wilde

Real-world quantum systems interact with their environments, leading to the irreversible dynamics described by the Lindblad equation. Solutions to the Lindblad equation give rise to quantum channels $\Phi_t$ that characterize the evolution…

Quantum Physics · Physics 2025-03-07 L. Y. Visser , R. J. P. T. de Keijzer , O. Tse , S. J. J. M. F. Kokkelmans

Despite the numerous uses of semidefinite programming (SDP) and its universal solvability via interior point methods (IPMs), it is rarely applied to practical large-scale problems. This mainly owes to the computational cost of IPMs that…

Optimization and Control · Mathematics 2024-03-19 Yifan Ran , Stefan Vlaski , Wei Dai
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