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We use neural networks to represent the characteristic function of many-body Gaussian states in the quantum phase space. By a pullback mechanism, we model transformations due to unitary operators as linear layers that can be cascaded to…

Quantum Physics · Physics 2021-10-19 Claudio Conti

Ultrafast electronic dynamics are typically studied using pulsed lasers. We demonstrate a complementary experimental approach: quantum simulation of ultrafast dynamics using trapped ultracold atoms. Counter-intuitively, this technique…

A growing cohort of experimental linear photonic networks implementing Gaussian boson sampling (GBS) have now claimed quantum advantage. However, many open questions remain on how to effectively verify these experimental results, as…

Quantum Physics · Physics 2023-08-03 Alexander S. Dellios , Margaret D. Reid , Peter D. Drummond

Strongly-coupled gauge theories far from equilibrium may exhibit unique features that could illuminate the physics of the early universe and of hadron and ion colliders. Studying real-time phenomena has proven challenging with…

Exploiting quantum properties to outperform classical ways of information-processing is an outstanding goal of modern physics. A promising route is quantum simulation, which aims at implementing relevant and computationally hard problems in…

Tensor network theory and quantum simulation are respectively the key classical and quantum computing methods in understanding quantum many-body physics. Here, we introduce the framework of hybrid tensor networks with building blocks…

Quantum Physics · Physics 2021-09-02 Xiao Yuan , Jinzhao Sun , Junyu Liu , Qi Zhao , You Zhou

The control of internal and motional quantum degrees of freedom of laser cooled trapped ions has been subject to intense theoretical and experimental research for about three decades. In the realm of quantum information science the ability…

Quantum Physics · Physics 2015-05-13 Michael Johanning , Andres Varon , Christof Wunderlich

We reduce measurement errors in a quantum computer using machine learning techniques. We exploit a simple yet versatile neural network to classify multi-qubit quantum states, which is trained using experimental data. This flexible approach…

Identifying and extracting the past information relevant to the future behaviour of stochastic processes is a central task in the quantitative sciences. Quantum models offer a promising approach to this, allowing for accurate simulation of…

Quantum Physics · Physics 2019-06-26 Qing Liu , Thomas. J. Elliott , Felix. C. Binder , Carlo Di Franco , Mile Gu

Quantum simulation with adiabatic annealing can provide insight into difficult problems that are impossible to study with classical computers. However, it deteriorates when the systems scale up due to the shrinkage of the excitation gap and…

Experimental quantum simulators have become large and complex enough that discovering new physics from the huge amount of measurement data can be quite challenging, especially when little theoretical understanding of the simulated model is…

Quantum Physics · Physics 2020-12-08 Alexander Lidiak , Zhexuan Gong

Simulating quantum mechanics is known to be a difficult computational problem, especially when dealing with large systems. However, this difficulty may be overcome by using some controllable quantum system to study another less controllable…

Quantum Physics · Physics 2014-03-14 I. M. Georgescu , S. Ashhab , Franco Nori

A custom-built and precisely controlled quantum system may offer access to a fundamental understanding of another, less accessible system of interest. A universal quantum computer is currently out of reach, but an analog quantum simulator…

Quantum computing promises to revolutionize several scientific and technological domains through fundamentally new ways of processing information. Among its most compelling applications is digital quantum simulation, where quantum computers…

Quantum Physics · Physics 2026-02-05 Laurin E. Fischer

We demonstrate quantum simulations of strongly correlated nuclear many-body systems on the RIKEN-Quantinuum Reimei trapped-ion quantum computer, targeting ground states of oxygen, calcium, and nickel isotopes. By combining a hard-core-boson…

Nuclear Theory · Physics 2026-02-10 Sota Yoshida , Takeshi Sato , Takumi Ogata , Masaaki Kimura

Classical stochastic processes can be generated by quantum simulators instead of the more standard classical ones, such as hidden Markov models. One reason for using quantum simulators is that they generally require less memory than their…

Quantum Physics · Physics 2016-09-19 C. Aghamohammadi , J. R. Mahoney , J. P. Crutchfield

We conduct experimental simulations of many body quantum systems using a \emph{hybrid} classical-quantum algorithm. In our setup, the wave function of the transverse field quantum Ising model is represented by a restricted Boltzmann…

Quantum Physics · Physics 2018-12-05 Bartłomiej Gardas , Marek M. Rams , Jacek Dziarmaga

Configurable arrays of optically trapped Rydberg atoms are a versatile platform for quantum computation and quantum simulation, also allowing controllable decoherence. We demonstrate theoretically, that they also enable proof-of-principle…

Quantum Physics · Physics 2025-11-06 Kaustav Mukherjee , Johannes Schachenmayer , Shannon Whitlock , Sebastian Wüster

Digital quantum simulation uses the capabilities of quantum computers to determine the dynamics of quantum systems, which are beyond the computability of modern classical computers. A notoriously challenging task in this field is the…

Quantum Physics · Physics 2021-04-19 Benedikt Fauseweh , Jian-Xin Zhu

Laser-cooled and trapped atomic ions form an ideal standard for the simulation of interacting quantum spin models. Effective spins are represented by appropriate internal energy levels within each ion, and the spins can be measured with…