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The Gottesman-Kitaev-Preskill (GKP) coding is proven to be a good candidate for encoding a qubit on continuous variables (CV) since it is robust under random-shift disturbance. Its preparation in optical systems, however, is challenging to…

Quantum Physics · Physics 2024-12-24 Fattah Sakuldee

Quantum algorithms require accurate representations of electronic states on a quantum device, yet the approximation of electronic wave functions for strongly correlated systems remains a profound theoretical challenge, with existing methods…

Quantum Physics · Physics 2025-04-29 Dipanjali Halder , Dibyendu Mondal , Rahul Maitra

Quantum machine learning is a rapidly advancing discipline that leverages the features of quantum mechanics to enhance the performance of computational tasks. Quantum reservoir processing, which allows efficient optimization of a single…

Recently it has been proposed to construct quantum error-correcting codes that embed a finite-dimensional Hilbert space in the infinite-dimensional Hilbert space of a system described by continuous quantum variables [D. Gottesman et al.,…

Quantum Physics · Physics 2007-05-23 Stefano Pirandola , Stefano Mancini , David Vitali , Paolo Tombesi

We present efficient circuits that can be used for the phase space tomography of quantum states. The circuits evaluate individual values or selected averages of the Wigner, Kirkwood and Husimi distributions. These quantum gate arrays can be…

Quantum Physics · Physics 2009-11-10 Juan Pablo Paz , Augusto J. Roncaglia , Marcos Saraceno

Classical algorithms for predicting the equilibrium geometry of strongly correlated molecules require expensive wave function methods that become impractical already for few-atom systems. In this work, we introduce a variational quantum…

In this paper, we propose efficient probabilistic algorithms for several problems regarding the autocorrelation spectrum. First, we present a quantum algorithm that samples from the Walsh spectrum of any derivative of $f()$. Informally, the…

Quantum Physics · Physics 2019-10-09 Debajyoti Bera , Subhamoy Maitra , SAPV Tharrmashastha

The complexity of semiparametric models poses new challenges to statistical inference and model selection that frequently arise from real applications. In this work, we propose new estimation and variable selection procedures for the…

Statistics Theory · Mathematics 2011-03-09 Bo Kai , Runze Li , Hui Zou

We demonstrate a fast, robust and non-destructive protocol for quantum state estimation based on continuous weak measurement in the presence of a controlled dynamical evolution. Our experiment uses optically probed atomic spins as a…

Quantum Physics · Physics 2009-11-13 Greg A. Smith , Andrew Silberfarb , Ivan H. Deutsch , Poul S. Jessen

The method of stable random projections is a tool for efficiently computing the $l_\alpha$ distances using low memory, where $0<\alpha \leq 2$ is a tuning parameter. The method boils down to a statistical estimation task and various…

Machine Learning · Computer Science 2008-12-18 Ping Li

Upsampling of time series data is often associated with classical fast Fourier transform analysis, but it also can be employed in the preparation of a quantum state vector. The quantum circuit of preparation derived from functional data…

Quantum Physics · Physics 2025-04-28 R. P. Erickson

Using a recent result of Albini et al. to represent quantum homodyne tomography in terms of a single observable (as a normalized positive operator measure) we construct a generalized Markov kernel which transforms (the measurement outcome…

Quantum Physics · Physics 2015-05-13 Pekka Lahti , Juha-Pekka Pellonpää

Numerical simulation of continuous variable quantum state preparation is a necessary tool for optimization of existing quantum information processing protocols. A powerful instrument for such simulation is the numerical computation in the…

Quantum Physics · Physics 2022-10-10 Jan Provazník , Radim Filip , Petr Marek

We show that quantum mechanics can be represented as an asymptotic projection of statistical mechanics of classical fields. Thus our approach does not contradict to a rather common opinion that quantum mechanics could not be reduced to…

Quantum Physics · Physics 2009-11-11 Andrei Khrennikov

After a brief introduction to the spectral presheaf, which serves as an analogue of state space in the topos approach to quantum theory, we show that every state of the von Neumann algebra of physical quantities of a quantum system…

Quantum Physics · Physics 2013-12-06 A. Doering

We propose a quantum algorithm to solve systems of nonlinear differential equations. Using a quantum feature map encoding, we define functions as expectation values of parametrized quantum circuits. We use automatic differentiation to…

Quantum Physics · Physics 2021-05-20 Oleksandr Kyriienko , Annie E. Paine , Vincent E. Elfving

In the current noisy intermediate scale quantum era of quantum computation, available hardware is severely limited by both qubit count and noise levels, precluding the application of many current hybrid quantum-classical algorithms to…

Quantum Physics · Physics 2024-03-05 Maria-Andreea Filip

The article undertakes the problem of pure state estimation from projective measurements based on photon counting. Two generic frames for qubit tomography are considered -- one composed of the elements of the SIC-POVM and the other defined…

Quantum Physics · Physics 2021-03-02 Artur Czerwinski

Conventional tomographic techniques are becoming increasingly infeasible for reconstructing the operators of quantum devices of growing sophistication. We describe a novel tomographic procedure using coherent states which begins by…

Quantum Physics · Physics 2012-11-08 L. Zhang , A. Datta , H. B. Coldenstrodt-Ronge , X. -M. Jin , J. Eisert , M. B. Plenio , I. A. Walmsley

Quantum simulation of materials is a promising application area of quantum computers. To practically realize this promise, we must reduce quantum resources while maintaining accuracy. In electronic structure calculations on classical…

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