Phys. Rev. X 14, 021007 (2024) – Published 8 April 2024
A novel theoretical framework unravels how processes in complex systems that occur at different timescales are coupled together at the functional level by sharing information.
M. Reza Rahimi Tabar, Farnik Nikakhtar, Laya Parkavousi, Amin Akhshi, Ulrike Feudel, and Klaus Lehnertz
Phys. Rev. X 14, 011050 (2024) – Published 18 March 2024
An innovative approach for analyzing complex systems sets the stage for a detailed understanding of the directions and strengths of pairwise and higher-order interactions in many fields ranging from neuroscience to finance to ecology.
Researchers have determined the amount of transverse orbital angular momentum that a type of optical vortex carries per photon, an important step for future applications.
Logan A. Becker, Baowang Li, Nicholas J. Priebe, Eyal Seidemann, and Thibaud Taillefumier
Phys. Rev. X 14, 011021 (2024) – Published 16 February 2024
Achieving realistic subthreshold variability in a biophysical neuronal model requires low-level synchrony in its synaptic input drive, a finding that challenges current theories to explain spiking activity in cortical neurons.
Tanguy Marchand, Misaki Ozawa, Giulio Biroli, and Stéphane Mallat
Phys. Rev. X 13, 041038 (2023) – Published 30 November 2023
A new multiscale approach allows for estimating high-dimensional probability distributions and fast sampling of many-body systems in various domains, from statistical physics to cosmology.
Claudia Merger, Alexandre René, Kirsten Fischer, Peter Bouss, Sandra Nestler, David Dahmen, Carsten Honerkamp, and Moritz Helias
Phys. Rev. X 13, 041033 (2023) – Published 20 November 2023
Models of systems in physics usually start with elementary processes. New work with a neural network shows how models can also be built by observing the system as a whole and deducing the underlying interactions.
Phys. Rev. X 13, 031020 (2023) – Published 18 August 2023
A wide class of physical systems could be turned into learning machines, thanks to a new general approach to training them based entirely on physical dynamics combined with a time-reversal operation.
Pablo Gottheil, Jürgen Lippoldt, Steffen Grosser, Frédéric Renner, Mohamad Saibah, Dimitrij Tschodu, Anne-Kathrin Poßögel, Anne-Sophie Wegscheider, Bernhard Ulm, Kay Friedrichs, Christoph Lindner, Christoph Engel, Markus Löffler, Benjamin Wolf, Michael Höckel, Bahriye Aktas, Hans Kubitschke, Axel Niendorf, and Josef A. Käs
Phys. Rev. X 13, 031003 (2023) – Published 10 July 2023
Kirsten Engbring, Dima Boriskovsky, Yael Roichman, and Benjamin Lindner
Phys. Rev. X 13, 021034 (2023) – Published 12 June 2023
A new test for determining whether time-series data is Markovian overcomes limitations of existing techniques and lays a foundation for the simple classification of diverse nonequilibrium systems.
Maria Chiara Angelini and Federico Ricci-Tersenghi
Phys. Rev. X 13, 021011 (2023) – Published 20 April 2023
A new theory, supported by large-scale numerical simulations, explores the conditions under which two Monte Carlo–based optimization algorithms can extract a signal from noisy data.
Phys. Rev. X 13, 011013 (2023) – Published 3 February 2023
A new, unified thermodynamic theory reveals an intimate relationship between optimal transport distances and stochastic and quantum thermodynamics in discrete-state systems.
A. Yogo, Z. Lan, Y. Arikawa, Y. Abe, S. R. Mirfayzi, T. Wei, T. Mori, D. Golovin, T. Hayakawa, N. Iwata, S. Fujioka, M. Nakai, Y. Sentoku, K. Mima, M. Murakami, M. Koizumi, F. Ito, J. Lee, T. Takahashi, K. Hironaka, S. Kar, H. Nishimura, and R. Kodama
Phys. Rev. X 13, 011011 (2023) – Published 31 January 2023
Experiments identify the mechanism that accelerates ions in a laser-driven neutron source (LDNS) as well as a scaling law for the neutron yield, key insights that move LDNS closer to practical neutron generation.
A waveguide sculpted in air with lasers transmits light over a distance of nearly 50 meters, which is 60 times farther than previous air-waveguide schemes.
Daoyuan Qian, Timothy J. Welsh, Nadia A. Erkamp, Seema Qamar, Jonathon Nixon-Abell, Georg Krainer, Peter St. George-Hyslop, Thomas C. T. Michaels, and Tuomas P. J. Knowles
Phys. Rev. X 12, 041038 (2022) – Published 30 December 2022
A new method for determining the ratios and interaction strengths among compounds that form biomolecular condensates relies on measurements of just one solute in one phase.
David B. Brückner, Matthew Schmitt, Alexandra Fink, Georg Ladurner, Johannes Flommersfeld, Nicolas Arlt, Edouard Hannezo, Joachim O. Rädler, and Chase P. Broedersz
Phys. Rev. X 12, 031041 (2022) – Published 20 September 2022
A bacterial genome’s evolution under changing drug concentrations displays effects of memory formation and mimics how disordered solids respond to external forces.
Scientists may have answered a longstanding question in biophysics: how the brain learns to recognize features in images before a newborn even opens its eyes.