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Magic states are the resource that allows quantum computers to attain an advantage over classical computers. This resource consists in the deviation from a property called stabilizerness which in turn implies that stabilizer circuits can be…

Quantum Physics · Physics 2022-12-26 Salvatore F. E. Oliviero , Lorenzo Leone , Alioscia Hamma , Seth Lloyd

Quantum Fourier analysis is an important topic in mathematical physics. We introduce a systematic protocol for testing and measuring ``magic'' in quantum states and gates, using a quantum Fourier approach. Magic, as a quantum resource, is…

Quantum Physics · Physics 2025-09-03 Kaifeng Bu , Weichen Gu , Arthur Jaffe

Understanding the computational complexity of quantum states is a central challenge in quantum many-body physics. In qubit systems, fermionic Gaussian states can be efficiently simulated on classical computers and hence can be employed as a…

Quantum Physics · Physics 2026-01-07 Piotr Sierant , Paolo Stornati , Xhek Turkeshi

To date all self-tests for high dimensional systems are confined to many-qubit states. This is due to two restrictions in the literature: the standard techniques for proving self-testing results apply only to qubits, and there are few…

Quantum Physics · Physics 2016-08-18 Matthew McKague

We establish the potential of continuous-variable Gaussian states of linear dynamical systems for machine learning tasks. Specifically, we consider reservoir computing, an efficient framework for online time series processing. As a…

Recent results have established dramatic advantages in learning properties of quantum states when a quantum computer is available to process or jointly measure multiple copies of the unknown quantum state. Learning tasks can be accomplished…

Quantum Physics · Physics 2026-05-08 Spencer Dimitroff , John Kallaugher , Ashe Miller , Mohan Sarovar

Magic, also known as nonstabilizerness, quantifies the distance of a quantum state to the set of stabilizer states, and it serves as a necessary resource for potential quantum advantage over classical computing. In this work, we study magic…

Quantum Physics · Physics 2025-10-23 Poetri Sonya Tarabunga , Emanuele Tirrito

Positive semi-definite matrices commonly occur as normal matrices of least squares problems in statistics or as kernel matrices in machine learning and approximation theory. They are typically large and dense. Thus algorithms to solve…

Numerical Analysis · Mathematics 2020-12-01 Markus Hegland , Frank deHoog

The quantum systems with finite-dimensional Hilbert space have several applications and are intensively explored theoretically and experimentally. The mathematical description of these systems follows the analogy with the usual…

Quantum Physics · Physics 2023-05-30 Nicolae Cotfas

Gaussian states and measurements collectively are not powerful-enough resources for quantum computing, as any Gaussian dynamics can be simulated efficiently, classically. However, it is known that any one non-Gaussian resource -- either a…

Quantum Physics · Physics 2021-12-17 Christos N. Gagatsos , Saikat Guha

Quantum metrology aims to enhance measurement precision beyond the standard quantum limit (SQL), the benchmark set by classical resources, enabling advances in sensing, imaging, and fundamental physics. A critical milestone beyond the SQL…

Quantum Physics · Physics 2025-08-19 Kimin Park , Tanjung Krisnanda , Yvonne Gao , Radim Filip

Characterizing quantum magic -- the resource enabling computational advantage beyond stabilizer circuits -- is subtle in qubit systems because established measures can give conflicting information about the same state. We introduce C(rho),…

Quantum Physics · Physics 2026-03-25 Soumyojyoti Dutta , Tushar

An analysis is conducted of the multipartite entanglement for Gaussian states generated by the parametric down-conversion of a femtosecond frequency comb. Using a recently introduced method for constructing optimal entanglement criteria, a…

Quantum Physics · Physics 2015-02-16 S. Gerke , J. Sperling , W. Vogel , Y. Cai , J. Roslund , N. Treps , C. Fabre

We compute the quantum maximal correlation for bipartite Gaussian states of continuous-variable systems. Quantum maximal correlation is a measure of correlation with the monotonicity and tensorization properties that can be used to study…

Quantum Physics · Physics 2023-03-14 Salman Beigi , Saleh Rahimi-Keshari

Physical Gottesman-Kitaev-Preskill (GKP) states are inherently noisy as ideal ones would require infinite energy. While this is typically considered as a deficiency to be actively corrected, this work demonstrates that imperfect GKP…

Quantum Physics · Physics 2026-03-12 Fariba Hosseinynejad , Pavithran Iyer , Guillaume Dauphinais , David L. Feder

We show that states obtained from deep random Clifford circuits doped with non-Clifford phase gates (including T-gates and $\sqrt{\mathrm{T}}$-gates) can be disentangled completely, provided the number of non-Clifford gates is smaller or…

Quantum Physics · Physics 2026-01-08 Gerald E. Fux , Benjamin Béri , Rosario Fazio , Emanuele Tirrito

We consider Gaussian states of fermionic systems and study the action of the partial transposition on the density matrix. It is shown that, with a suitable choice of basis, these states are transformed into a linear combination of two…

Statistical Mechanics · Physics 2015-05-29 Viktor Eisler , Zoltan Zimboras

Recent results on the non-universality of fault-tolerant gate sets underline the critical role of resource states, such as magic states, to power scalable, universal quantum computation. Here we develop a resource theory, analogous to the…

Quantum Physics · Physics 2015-06-16 Victor Veitch , Seyed Ali Hamed Mousavian , Daniel Gottesman , Joseph Emerson

We establish tight upper and lower bounds for the Entanglement of Formation of an arbitrary two-mode Gaussian state employing necessary properties of Gaussian channels. Both bounds are strictly given by the Entanglement of Formation of…

Quantum Physics · Physics 2014-06-09 Fernando Nicacio , Marcos Cesar de Oliveira

Computing Gaussian ground states via variational optimization is challenging because the covariance matrices must satisfy the uncertainty principle, rendering constrained or Riemannian optimization costly, delicate, and thus difficult to…

Quantum Physics · Physics 2026-01-29 Christopher Willby , Tomohiro Hashizume , Jason Crain , Dieter Jaksch