World's Best Scientists 2026 revealed!
Orlando Ragnisco

Orlando Ragnisco

D-Index & Metrics

Mathematics

D-Index
39
Citations
4647
World Ranking
2250
National Ranking
66

Overview

Orlando Ragnisco is affiliated with Roma Tre University in Italy, specializing in mathematics. Their research spans several interconnected fields and subfields, notably geometry and topology, statistical and nonlinear physics, mathematical physics, renewable energy, sustainability, and the environment, as well as general agricultural and biological sciences.

The main academic topics addressed in their work include nonlinear waves and solitons, homotopy and cohomology in algebraic topology, geometry and complex manifolds, global energy and sustainability research, agriculture, land use, rural development, sustainable development, environmental policy, and geometric and algebraic topology.

Their publication record covers diverse venues, with multiple papers appearing in arXiv (Cornell University) and Open Communications in Nonlinear Mathematical Physics, alongside contributions to Ecological Economics and Symmetry. Notable recent papers include:

  • An Ecology and Economy Coupling Model. A global stationary state model for a sustainable economy in the Hamiltonian formalism, 2020, Ecological Economics
  • Time-Dependent Hamiltonian Mechanics on a Locally Conformal Symplectic Manifold, 2023, Symmetry
  • Time-dependent Hamiltonian mechanics on a locally conformal symplectic manifold, 2021, arXiv (Cornell University)
  • The Volterra Integrable case. Novel analytical and numerical results, 2024, arXiv (Cornell University)
  • The Volterra Integrable case. Novel analytical and numerical results, 2024, Open Communications in Nonlinear Mathematical Physics

Orlando Ragnisco collaborates frequently with several researchers. Key co-authors include Massimo Scalia, Federico Zullo, Cristina Sardón, B. Tirozzi, and Aurelio Angelini. These collaborations have contributed to papers in multiple subfields of study and research topics.

Best Publications

  • Integrable symplectic maps

    M. Bruschi;M. Bruschi;O. Ragnisco;O. Ragnisco;P. M. Santini;Tu Gui-Zhang

  • Exact solution of the classical and quantal one-dimensional many-body problems with the two-body potential {ie383-01}

    P. Calogero;O. Ragnisco;C. Marchioro

  • A systematic construction of completely integrable Hamiltonians from coalgebras

    Angel Ballesteros;Orlando Ragnisco

  • R-Matrices and Higher Poisson Brackets for Integrable Systems

    Walter Oevel;Orlando Ragnisco;Orlando Ragnisco

  • Reduction techniques for infinite-dimensional Hamiltonian systems: some ideas and applications

    F Magri;C Morosi;Orlando Ragnisco;Orlando Ragnisco

  • Perturbative approach to some one-dimensional many-body problems. I: Discussion of the Rayleigh-Schrödinger and Brillouin-Wigner series for the Sutherland model

    D. Levi;O. Ragnisco

  • Integrable time-discretisation of the Ruijsenaars-Schneider model

    Fw Nijhoff;Orlando Ragnisco;Vb Kuznetsov

  • Quantum mechanics on spaces of nonconstant curvature: The oscillator problem and superintegrability

    Ángel Ballesteros;Alberto Enciso;Francisco J. Herranz;Orlando Ragnisco

  • DRESSING METHOD VS CLASSICAL DARBOUX TRANSFORMATION

    Decio Levi;Orlando Ragnisco;A. Sym

  • The nonabelian Toda lattice: Discrete analogue of the matrix Schrödinger spectral problem

    M Bruschi;Sv Manakov;Orlando Ragnisco;Decio Levi

  • A NOVEL HIERARCHY OF INTEGRABLE LATTICES

    I Merola;O Ragnisco;Tu Gui-Zhang

  • CONTINUOUS AND DISCRETE MATRIX BURGERS' HIERARCHIES

    D. Levi;O. Ragnisco;M. Bruschi

  • A Novel Hierarchy of Integrable Lattices

    I.Merola;O.Ragnisco;Tu Gui Zhang

  • Peakons, r-matrix and Toda lattice

    Orlando Ragnisco;Orlando Ragnisco;M. Bruschi;M. Bruschi

  • Lax representation and complete integrability for the periodic relativistic Toda lattice

    M Bruschi;Orlando Ragnisco

  • Mastersymmetries, angle variables, and recursion operator of the relativistic Toda lattice

    Walter Oevel;Benno Fuchssteiner;Hongwei Zhang;Orlando Ragnisco

  • Non-isospectral deformations and Darboux transformations for the third-order spectral problem

    Decio Levi;Orlando Ragnisco

  • Bäcklund transformation vs. the dressing method

    Decio Levi;Orlando Ragnisco;A. Sym

  • RECURSION OPERATOR AND BACKLUND-TRANSFORMATIONS FOR THE RUIJSENAARS-TODA LATTICE

    M Bruschi;M Bruschi;Orlando Ragnisco;Orlando Ragnisco

  • A maximally superintegrable system on an n-dimensional space of nonconstant curvature

    Angel Ballesteros;Alberto Enciso;Francisco J. Herranz;Orlando Ragnisco

  • Restricted flows of the AKNS hierarchy

    Orlando Ragnisco;S. Rauchwojciechowski

Frequent Co-Authors

Angel Ballesteros
Angel Ballesteros University of Burgos
Decio Levi
Decio Levi Roma Tre University
Francisco J. Herranz
Francisco J. Herranz University of Burgos
Frank W. Nijhoff
Frank W. Nijhoff University of Leeds
Mariano Santander
Mariano Santander University of Valladolid
Ryu Sasaki
Ryu Sasaki Tokyo University of Science
Paolo Maria Santini
Paolo Maria Santini University of Parma
Benno Fuchssteiner
Benno Fuchssteiner University of Paderborn

External Links

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students pursuing Mathematics in the USA, exploring complementary online degrees can expand career opportunities. One popular option is enrolling in year long MBA programs, which provide valuable business acumen alongside analytical skills.

Many prospective students wonder if they can advance their education faster—especially by transferring existing credits. Resources outlining can you transfer MBA credits offer guidance on how to maximize prior coursework toward an MBA, making the path more flexible and efficient.

Mathematics graduates often specialize in data-heavy fields. Programs focused on data analysis programs are ideal for applying mathematical theories to big data, predictive modeling, and decision-making—a growing area in many industries.

For those looking to balance rigor with accessibility, exploring the easiest MBA programs can provide a practical entry point into business studies without compromising career growth potential.

Best Scientists Citing Orlando Ragnisco

Trending Scientists

Recently Published Articles