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Related papers: Spin models and boson sampling

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Recent experiments demonstrated quantum computational advantage in random circuit sampling and Gaussian boson sampling. However, it is unclear whether these experiments can lead to practical applications even after considerable research…

Quantum Physics · Physics 2023-12-14 Chae-Yeun Park , Pablo A. M. Casares , Juan Miguel Arrazola , Joonsuk Huh

This article presents numerical recipes for simulating high-temperature and non-equilibrium quantum spin systems that are continuously measured and controlled. The notion of a spin system is broadly conceived, in order to encompass…

Optical losses are the main obstacle to demonstrating a quantum advantage via boson sampling without leaving open the possibility of classical spoofing. We propose a method for generating low-depth optical circuits suitable for boson…

Quantum Physics · Physics 2021-10-12 R. van der Meer , S. Huber , P. W. H. Pinkse , R. García-Patrón , J. J. Renema

Full insight into the dynamics of a coupled quantum system depends on the ability to follow the effect of a local excitation in real-time. Here, we trace the coherent evolution of a pair of coupled atomic spins by means of scanning…

Since its introduction Boson Sampling has been the subject of intense study in the world of quantum computing. The task is to sample independently from the set of all $n \times n$ submatrices built from possibly repeated rows of a larger $m…

Quantum Physics · Physics 2020-05-27 Peter Clifford , Raphaël Clifford

We employ so-called quantum kernel estimation to exploit complex quantum dynamics of solid-state nuclear magnetic resonance for machine learning. We propose to map an input to a feature space by input-dependent Hamiltonian evolution, and…

Quantum Physics · Physics 2022-03-14 Takeru Kusumoto , Kosuke Mitarai , Keisuke Fujii , Masahiro Kitagawa , Makoto Negoro

If classical algorithms have been successful in reproducing the estimation of expectation values of observables of some quantum circuits using off-the-shelf computing resources, matching the performance of the most advanced quantum devices…

The spin-boson (SB) model is a standard prototype for quantum dissipation, which we generalize in this work, to explore the dissipative effects on a one-dimensional spin-orbit (SO) coupled particle in the presence of a sub-ohmic bath. We…

Statistical Mechanics · Physics 2026-02-02 Sudip Sinha , Subhasis Sinha , Sushanta Dattagupta

We extend our study of Motion Planning via Manifold Samples (MMS), a general algorithmic framework that combines geometric methods for the exact and complete analysis of low-dimensional configuration spaces with sampling-based approaches…

Robotics · Computer Science 2015-09-17 Oren Salzman , Michael Hemmer , Dan Halperin

We consider a spin-boson Hamiltonian which is generalized such that the Hamiltonians for the system ($\hat{H}_{\cal S}$) and the interaction with the environment ($\hat{H}_{\rm int}$) do not commute with each other. Considering a…

Quantum Physics · Physics 2015-03-19 Hoofar Daneshvar , G. W. F. Drake

When probing nuclear spins in materials on the nanometer scale, random fluctuations of the spin polarization will exceed the mean Boltzmann polarization for sample volumes below about (100nm)^3. In this work, we use magnetic resonance force…

Mesoscale and Nanoscale Physics · Physics 2008-01-14 C. L. Degen , M. Poggio , H. J. Mamin , D. Rugar

Boson sampling is one of the leading protocols for demonstrating a quantum advantage, but the theory of how this protocol responds to noise is still incomplete. We extend the theory of classical simulation of boson sampling with partial…

Quantum Physics · Physics 2025-03-07 S. N. van den Hoven , E. Kanis , J. J. Renema

We show that the nonlinear stochastic dynamics of a measurement-feedback-based coherent Ising machine (MFB-CIM) in the presence of quantum noise can be exploited to sample degenerate ground and low-energy spin configurations of the Ising…

Numerical modelling of coherent spin relaxation in nanomagnets, formed by magnetic molecules of high spins, is accomplished. Such a coherent spin dynamics can be realized in the presence of a resonant electric circuit coupled to the magnet.…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 V. I. Yukalov , V. K. Henner , P. V. Kharebov

Boson sampling is a promising candidate for quantum supremacy. It requires to sample from a complicated distribution, and is trusted to be intractable on classical computers. Among the various classical sampling methods, the Markov chain…

We present a modular approach to reinforcement learning that uses a Bayesian representation of the uncertainty over models. The approach, BOSS (Best of Sampled Set), drives exploration by sampling multiple models from the posterior and…

Machine Learning · Computer Science 2012-05-14 John Asmuth , Lihong Li , Michael L. Littman , Ali Nouri , David Wingate

Atomistic simulations of thermodynamic properties of magnetic materials rely on an accurate modelling of magnetic interactions and an efficient sampling of the high-dimensional spin space. Recent years have seen significant progress with a…

Statistical Mechanics · Physics 2019-03-27 Ning Wang , Thomas Hammerschmidt , Jutta Rogal , Ralf Drautz

We reformulate the full quantum dynamics of spin systems using a phase space representation based on SU(2) coherent states which generates an exact mapping of the dynamics of any spin system onto a set of stochastic differential equations.…

Statistical Mechanics · Physics 2013-10-10 Ray Ng , Piotr Deuar , Erik Sorensen

With extensive variational simulations, dissipative quantum phase transitions in the sub-Ohmic spin-boson model are numerically studied in a dense limit of environmental modes. By employing a generalized trial wave function composed of…

Statistical Mechanics · Physics 2023-09-06 Yulong Shen , Nengji Zhou

Computer simulations have become an important tool across the biomedical sciences and beyond. For many important problems several different models or hypotheses exist and choosing which one best describes reality or observed data is not…

Quantitative Methods · Quantitative Biology 2010-01-20 Tina Toni , Michael P. H. Stumpf
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