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Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insight by isolating the essential degrees of freedom that dictate the…

Statistical Mechanics · Physics 2023-04-12 Shriram Chennakesavalu , David J. Toomer , Grant M. Rotskoff

Quantum state tomography, which aims to find the best description of a quantum state -- the density matrix, is an essential building block in quantum computation and communication. Standard techniques for state tomography are incapable of…

Quantum Physics · Physics 2022-11-18 Markus Rambach , Akram Youssry , Marco Tomamichel , Jacquiline Romero

In bulk quantum computation one can manipulate a large number of indistinguishable quantum computers by parallel unitary operations and measure expectation values of certain observables with limited sensitivity. The initial state of each…

Quantum Physics · Physics 2009-10-30 Emanuel Knill , Isaac Chuang , Raymond Laflamme

Molecular dynamics simulations provide theoretical insight into the microscopic behavior of materials in condensed phase and, as a predictive tool, enable computational design of new compounds. However, because of the large temporal and…

Chemical Physics · Physics 2020-06-18 Wujie Wang , Rafael Gómez-Bombarelli

In this paper we introduce a canonical quantum coarse-graining and use negentropy to connect ignorance as measured by quantum information entropy and ignorance related to quantum coarse-graining. For our procedure, macro-states are the set…

Quantum Physics · Physics 2021-11-16 Shannon Ray , Paul M. Alsing , Carlo Cafaro , Shelton Jacinto

We present methods and results of shot-by-shot correlation of noisy measurements to extract entangled state and process tomography in a superconducting qubit architecture. We show that averaging continuous values, rather than counting…

Solving large systems of equations is a challenge for modeling natural phenomena, such as simulating subsurface flow. To avoid systems that are intractable on current computers, it is often necessary to neglect information at small scales,…

Quantum state smoothing is a technique for assigning a valid quantum state to a partially observed dynamical system, using measurement records both prior and posterior to an estimation time. We show that the technique is greatly simplified…

Quantum Physics · Physics 2025-09-09 Kiarn T. Laverick , Areeya Chantasri , Howard M. Wiseman

Quantum error correction protocols have been developed to offset the high sensitivity to noise inherent in quantum systems. However, much is still unknown about the behaviour of a quantum error-correcting code under general noise, including…

Quantum Physics · Physics 2021-06-09 Stefanie J. Beale , Joel J. Wallman

Phase estimation is the most investigated protocol in quantum metrology, but its performance is affected by the presence of noise, also in the form of imperfect state preparation. Here we discuss how to address this scenario by using a…

The common idea behind complexity reduction in physical systems is separation of information into "physically meaningful" and "safely ignorable". Here we consider a generic notion of such separation -- implemented by coarse-graining the…

Quantum Physics · Physics 2018-06-04 Oleg Kabernik

Constructing an integrated large-scale qubit system of realistic size requires addressing the challenge of physical crowding among qubits. This constraint poses an issue of coarse-grained (CG) measurement, wherein information from the…

Quantum Physics · Physics 2024-04-10 Donghun Jung , Young-Wook Cho , Yosep Kim , Junghyun Lee

The primary objective of this work is to develop coarse-graining schemes for stochastic many-body microscopic models and quantify their effectiveness in terms of a priori and a posteriori error analysis. In this paper we focus on stochastic…

Numerical Analysis · Mathematics 2007-05-23 Markos A. Katsoulakis , Petr Plechac , Luc Rey-Bellet , Dimitrios K. Tsagkarogiannis

When noisy intermediate scalable quantum (NISQ) devices are applied in information processing, all of the stages through preparation, manipulation, and measurement of multipartite qubit states contain various types of noise that are…

Quantum Physics · Physics 2021-12-16 Hyeokjea Kwon , Joonwoo Bae

In this paper, we explore an efficient online algorithm for quantum state estimation based on a matrix-exponentiated gradient method previously used in the context of machine learning. The state update is governed by a learning rate that…

Quantum Physics · Physics 2019-03-28 Akram Youssry , Christopher Ferrie , Marco Tomamichel

Learning problems involving quantum data are natural candidates for demonstrating an advantage in quantum machine learning. Recent results indicate that, for certain tasks and under noiseless conditions, coherent processing of quantum data…

We propose a quantum tomography scheme for pure qudit systems which adopts random base measurements and generative learning methods, along with a built-in fidelity estimation approach to assess the reliability of the tomographic states. We…

Quantum Physics · Physics 2020-03-25 Jun Wang , Zhao-Yu Han , Song-Bo Wang , Zeyang Li , Liang-Zhu Mu , Heng Fan , Lei Wang

We present strictly efficient schemes for scalable measurement-based quantum computing using continuous-variable systems: These schemes are based on suitable non-Gaussian resource states, ones that can be prepared using interactions of…

Quantum Physics · Physics 2013-05-30 Matthias Ohliger , Jens Eisert

Our everyday descriptions of the universe are highly coarse-grained, following only a tiny fraction of the variables necessary for a perfectly fine-grained description. Coarse graining in classical physics is made natural by our limited…

Quantum Physics · Physics 2008-11-26 Murray Gell-Mann , James Hartle

Robust, accurate and efficient quantum tomography is key for future quantum technologies. Traditional methods are impractical for even medium sized systems and are not robust against noise and errors. Here we report on an experimental…

Quantum Physics · Physics 2016-07-27 Robert J. Chapman , Christopher Ferrie , Alberto Peruzzo