Computational science articles within Nature Physics

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  • Article |

    Cytoplasmic flows in the fruit fly oocyte can reorganize cellular components. These structured vortical flows arise through self-organizing dynamics of microtubules, molecular motors and cytoplasm.

    • Sayantan Dutta
    • , Reza Farhadifar
    •  & Michael J. Shelley

  • News & Views |

    Predicting the large-scale behaviour of complex systems is challenging because of their underlying nonlinear dynamics. Theoretical evidence now verifies that many complex systems can be simplified and still provide an insightful description of the phenomena of interest.

    • Jianxi Gao

  • Article |

    Although using low-rank matrices is the go-to approach to model the dynamics of complex systems, its validity remains formally unconfirmed. An analysis of random networks and real-world data now sheds light on this low-rank hypothesis and its implications.

    • Vincent Thibeault
    • , Antoine Allard
    •  & Patrick Desrosiers

  • Article |

    It has been suggested that Gaussian boson sampling may provide a quantum computational advantage for calculating the vibronic spectra of molecules. Now, an equally efficient classical algorithm has been identified.

    • Changhun Oh
    • , Youngrong Lim
    •  & Liang Jiang

  • Article |

    Being able to perform qubit measurements within a quantum circuit and adapt to their outcome broadens the power of quantum computers. These mid-circuit measurements have now been used to implement a cryptographic proof of non-classical behaviour.

    • Daiwei Zhu
    • , Gregory D. Kahanamoku-Meyer
    •  & Christopher Monroe

  • Article
    | Open Access

    Elastoviscoplastic fluids combine solid- and liquid-like behaviour depending on applied stress. Simulations of elastoviscoplastic fluids at high Reynolds number now show that plasticity plays a key role in the turbulent flows seen in these systems, leading for example to intermittency.

    • Mohamed S. Abdelgawad
    • , Ianto Cannon
    •  & Marco E. Rosti

  • Article |

    Quantum operations can be considered as points in a high-dimensional space in which distance reflects the similarity of two operations. Applying differential-geometric methods in this picture gives insights into the complexity of quantum systems.

    • Adam R. Brown

  • Research Briefing |

    The formation of bubbles at liquid–liquid interfaces is challenging to explain because gas pockets cannot be stabilized by cracks on solid impurities. Experiments show that a difference in the gas solubilities of two immiscible liquids provides a gas reservoir, which allows gas to accumulate at the interface, leading to bubble formation.

  • Comment |

    Fluid simulations today are remarkably realistic. In this Comment I discuss some of the most striking results from the past 20 years of computer graphics research that made this happen.

    • Károly Zsolnai-Fehér

  • News & Views |

    Experiments with ultracold atoms can be used to create nearly ideal quantum simulations of theoretical models. A realization of a model of exotic magnetism has tested the limits of what can be studied numerically on a classical computer.

    • Evgeny Kozik

  • Article |

    Uncovering structures in temporal networks requires different tools than in their static counterparts. A metric now quantifies whether the nodes with a large number of connections also tend to stay simultaneously connected for longer times.

    • Nicola Pedreschi
    • , Demian Battaglia
    •  & Alain Barrat

  • Article |

    Evaluations of quantum computers across architectures need reliable benchmarks. A class of benchmarks that can directly reflect the structure of any algorithm shows that different quantum computers have considerable variations in performance.

    • Timothy Proctor
    • , Kenneth Rudinger
    •  & Robin Blume-Kohout

  • Article |

    Many quantum machine learning algorithms have been proposed, but it is typically unknown whether they would outperform classical methods on practical devices. A specially constructed algorithm shows that a formal quantum advantage is possible.

    • Yunchao Liu
    • , Srinivasan Arunachalam
    •  & Kristan Temme

  • Letter |

    In general, it isn’t known when a quantum computer will have an advantage over a classical device. Now it’s proven that computers with limited working memory are more powerful if they are quantum.

    • Dmitri Maslov
    • , Jin-Sung Kim
    •  & Sarah Sheldon

  • Article |

    Quantum systems make it challenging to determine candidate Hamiltonians from experimental data. An automated protocol is presented and its capabilities to infer the correct Hamiltonian are demonstrated in a nitrogen-vacancy centre set-up.

    • Antonio A. Gentile
    • , Brian Flynn
    •  & Anthony Laing

  • Article |

    The ability to perform multiple tasks simultaneously is a key characteristic of parallel architectures. Using methods from statistical physics, this study provides analytical results that quantify the limitations of processing capacity for different types of tasks in neural networks.

    • Giovanni Petri
    • , Sebastian Musslick
    •  & Jonathan D. Cohen

  • News & Views |

    Quantum computing combines great promise with daunting challenges — the road to devices that solve real-world problems is still long. Now, an implementation of a quantum algorithm maps the problems we want to solve to the devices we already have.

    • Boaz Barak

  • Measure for Measure |

    Simulations are as much a part of science as hypothesis and experiment. But can their outcomes be considered observations? Wendy S. Parker investigates.

    • Wendy S. Parker

  • Comment |

    The uncertainty associated with epidemic forecasts is often simulated with ensembles of epidemic trajectories based on combinations of parameters. We show that the standard approach for summarizing such ensembles systematically suppresses critical epidemiological information.

    • Jonas L. Juul
    • , Kaare Græsbøll
    •  & Sune Lehmann

  • Article |

    The phrase ‘arrow of time’ refers to the asymmetry in the flow of events. A machine learning algorithm trained to infer its direction identifies entropy production as the relevant underlying physical principle in the decision-making process.

    • Alireza Seif
    • , Mohammad Hafezi
    •  & Christopher Jarzynski

  • News & Views |

    Near-term quantum computations are susceptible to noise that — left uncorrected — can destroy the correlations responsible for quantum computational speedups. New work develops tools for bolstering the noise resilience of these speedups.

    • Bill Fefferman

  • Comment |

    Automated learning from data by means of deep neural networks is finding use in an ever-increasing number of applications, yet key theoretical questions about how it works remain unanswered. A physics-based approach may help to bridge this gap.

    • Lenka Zdeborová

  • Article |

    A quantum circuit-based algorithm inspired by convolutional neural networks is shown to successfully perform quantum phase recognition and devise quantum error correcting codes when applied to arbitrary input quantum states.

    • Iris Cong
    • , Soonwon Choi
    •  & Mikhail D. Lukin

  • News & Views |

    A statistical analysis of data from ultra-relativistic heavy-ion collisions has uncovered the specific viscosities of the quark–gluon plasma — suggesting that the hottest matter in the current Universe behaves like a near-perfect fluid.

    • Kari J. Eskola

  • Article |

    Modelling and microscopy of thousands of cells together reveal the coupling through which the cell cycle influences the circadian clock. This coupling may explain why mammalian tissues growing at different rates have shifted circadian rhythms.

    • Colas Droin
    • , Eric R. Paquet
    •  & Felix Naef

  • Letter |

    Quantum gas microscopes provide high-resolution real-space snapshots of quantum many-body systems. Now machine-learning techniques are used in choosing theoretical descriptions according to the consistency of their predictions with these snapshots.

    • Annabelle Bohrdt
    • , Christie S. Chiu
    •  & Michael Knap

  • Measure for Measure |

    Artificial intelligence is set to rival the human mind, just as the engine did the horse. José Hernández-Orallo looks at how we compare cognitive performance.

    • José Hernández-Orallo

  • Article |

    Finding the relevant degrees of freedom of a system is a key step in any renormalization group procedure. But this can be difficult, particularly in strongly interacting systems. A machine-learning algorithm proves adept at identifying them for us.

    • Maciej Koch-Janusz
    •  & Zohar Ringel

  • Letter |

    A technique allows optimal inference of the structure of a network when the available observed data are rich but noisy, incomplete or otherwise unreliable.

    • M. E. J. Newman

  • Letter |

    Unsupervised machine learning techniques can efficiently perform quantum state tomography of large, highly entangled states with high accuracy, and allow the reconstruction of many-body quantities from simple experimentally accessible measurements.

    • Giacomo Torlai
    • , Guglielmo Mazzola
    •  & Giuseppe Carleo

  • News & Views |

    A type of optics experiment called a boson sampler could be among the easiest routes to demonstrating the power of quantum computers. But recent work shows that super-classical boson sampling may be a long way off.

    • Andrew M. Childs

  • Letter |

    A neural-network technique can exploit the power of machine learning to mine the exponentially large data sets characterizing the state space of condensed-matter systems. Topological transitions and many-body localization are first on the list.

    • Evert P. L. van Nieuwenburg
    • , Ye-Hua Liu
    •  & Sebastian D. Huber

  • Letter |

    The common policy of replacing infected individuals with healthy substitutes can have the effect of accelerating disease transmission. A dynamic network model suggests that standard modelling approaches underplay the effect of network structure.

    • Samuel V. Scarpino
    • , Antoine Allard
    •  & Laurent Hébert-Dufresne

  • News & Views |

    The dynamics of a viscous liquid undergo a dramatic slowdown when it is cooled to form a solid glass. Recognizing the structural changes across such a transition remains a major challenge. Machine-learning methods, similar to those Facebook uses to recognize groups of friends, have now been applied to this problem.

    • Michele Ceriotti
    •  & Vincenzo Vitelli

  • Letter |

    When general relativity is included in large-scale simulations of the cosmic structure of the Universe, relativistic effects turn out to be small but measurable, thus providing tests for models of dark matter and dark energy.

    • Julian Adamek
    • , David Daverio
    •  & Martin Kunz

  • Letter |

    The relation between structure and dynamics in glasses is not fully understood. A new approach based on machine learning now reveals a correlation between softness—a structural property—and glassy dynamics.

    • S. S. Schoenholz
    • , E. D. Cubuk
    •  & A. J. Liu

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