AQTIVATE Conference

Session

Invited

28 Sept 2026, 09:30

Sun Hall Hotel

2. Future HPC and Quantum Hardware

Thomas Lippert

28/09/2026, 09:30

3. TBD

Jiali Gao

28/09/2026, 10:15

4. Quantum Information

Sabrina Maniscalco

28/09/2026, 11:30

5. Biology

Ellinor Haglund

28/09/2026, 12:15

77. Computational Biophysics of Biomolecular Activation: From WAVE Complex Variants to GPCR Dynamics

Song Xie (Forschungszentrum Jülich)

28/09/2026, 17:00

Invited talk

Computer simulations can provide unique atomistic insights into the molecular mechanisms underlying protein activation. Here, I will focus on two neurobiologically relevant systems: the WAVE regulatory complex (WRC) and the adenosine A2A receptor (A2AR), a G protein-coupled receptor (GPCR). Molecular dynamics simulations of the WRC identified common mechanistic features of autism-associated...

75. Machine Learning and Lattice QCD

Jacob Friedrich Finkenrath (Bergische Universitaet Wuppertal (DE))

29/09/2026, 09:30

Invited talk

I will review some of the recent machine learning applications in the field of lattice QCD. Based on that, I will discuss there possible application within application of lattice field theory simulations.

13. Physics Aware Deep Learning

Patrick Gallinari

29/09/2026, 10:15

51. Small-scale alignment and clustering of heavy inertial fibers in turbulence

Chiara Calascibetta (Université Côte d'Azur, CNRS, INPHYNI & Inria, Nice, France)

29/09/2026, 11:30

Invited talk

The dynamics of non-spherical particles in turbulence are governed by the interplay between inertia and orientation-dependent hydrodynamic forces. We investigate rigid fibers dynamics by bridging two asymptotic descriptions: the small-size limit described by Jeffery’s equation, and the finite-length limit captured by slender-body theory. This framework enables systematic variation of aspect...

17. Comp. biology

Lipi Thukral

29/09/2026, 15:00

Invited talk

85. Making quantum machine learning separations more physical

Sofiene Jerbi (Freie Universität Berlin - Helmholtz Zentrum Berlin)

30/09/2026, 09:30

Invited talk

One of the core challenges of research in quantum computing is to understand whether quantum advantages can be found for problems of practical interest. In the field of quantum machine learning, we know for a few years now that proof-of-concept exponential advantages can be established in learning tasks derived from classically hard problems such as factoring or computing discrete logarithms....

42. A Principled Approach to Enhanced Sampling

MICHELE PARRINELLO (Fondazione istituto italiano di tecnologia)

30/09/2026, 10:15

Invited talk

Molecular Dynamics simulations are a valuable tool for investigating a wide variety of phenomena at the atomistic scale. However, it is this very high resolution that limits the time scales accessible to such simulations. Typically, this limitation is overcome by deploying methods that require knowledge of the system's metastable states and an approximation of the reaction coordinate, referred...

47. Lattice Boltzmann Algorithms for complex fluids and complex flows

Alessandro Gabbana (University of Ferrara / INFN Ferrara)

30/09/2026, 11:30

Invited talk

The Lattice Boltzmann Method (LBM) has evolved into one of the most versatile computational frameworks for simulating complex fluids and multiscale flow phenomena. Its kinetic formulation naturally accommodates multiphase and multicomponent flows, thermal transport, fluid–structure interactions, porous media flows, and turbulence, while offering excellent scalability on modern high-performance...

23. Physics HPC Lattice QCD

Simone Bacchio

30/09/2026, 12:15

24. Hadron Structure

Gunnar Bali

01/10/2026, 09:30

Invited talk

40. Quantum algorithms for classical fluids

Sauro Succi (Italian Institute of Technology)

01/10/2026, 10:15

Invited talk

In the recent years increasing attention has been directed towards the
the development of quantum algorithm for classical physics, most
notably fluid dynamics and other nonlinear transport phenomena.

Solving fluid dynamics on quantum computers is a steep challenge
on top of a challenge because, besides the notorious hurdles of
decoherence and loss of entanglement, the physics of...

26. Quantum Computing

Ilaria Siloi

01/10/2026, 11:30

Invited talk

78. New directions in interpreting AI models

Andreas Demou (The Cyprus Institute)

01/10/2026, 12:00

Invited talk

Mechanistic interpretability aspires to reverse engineer AI models by breaking down black-box weights and activations into human-understandable features and circuits. A leading approach for mechanistic interpretability is sparse dictionary learning, which trains an encoder to map activations into a sparse code and a decoder to reconstruct them. The corresponding architecture is called...

74. Physics-constrained diffusion model for synthesis of 3D turbulent data

Prof. Michele Buzzicotti (University of Rome Tor Vergata and INFN)

01/10/2026, 14:30

Invited talk

Synthesizing fully developed three-dimensional turbulent velocity fields remains a long-standing problem in fluid mechanics and an open challenge for generative modeling. This difficulty arises from the combination of extreme dimensionality, multiscale fluctuations, strong intermittency, and the need to satisfy exact physical constraints, including incompressibility and prescribed mass and...

76. Dynamics of metastable states in quantum systems

Luka Pavesic (University of Padova)

01/10/2026, 16:30

Invited talk

Metastable states appear across many areas of physics, from condensed matter to cosmology. Their relaxation is described by the semi-classical 'critical bubble theory', developed more than 50 years ago. Despite its broad applicability, the quantum version of the theory has little experimental support, and understanding the relaxation of metastable states in quantum many-body systems remains a...

34. Lattice QCD

Antonio Evangelista

01/10/2026, 17:00

Invited talk

57. Advances in Algebraic Multigrid Methods for PDEs

Jacob Schroder (University of New Mexico)

02/10/2026, 09:30

Invited talk

Algebraic multigrid (AMG) is a popular and effective solver for sparse linear systems arising from discretized partial differential equations (PDEs). The optimality and efficiency of AMG rests on the complementary relationship between relaxation (e.g., Gauss-Seidel) and interpolation, which when effective, results in optimal O($n$) scaling in the number of degrees-of-freedom $n$. Relaxation...

79. QM/MM MD simulations of proton-coupled transporters

Paolo Carloni (Forschungszentrum Jülich GmbH)

02/10/2026, 10:15

Invited talk

We will discuss some recent applications of our massively parallel QM/MM code MiMiC, developed within a consortium of european university. We will focus on transporters which exploit proton gradients across the membrane to transport organic molecules.
We will close with a perspective of using data science approaches to develop potentials and calculate accurate free energies using QM/MM MD data.

45. Hamiltonian methods from Quantum Information Technologies: from Z2 String Dynamics to Continuous U(1) Electrodynamics

Enrique Rico Ortega (CERN)

02/10/2026, 10:45

Invited talk

Real-time, non-perturbative dynamics of gauge theories, from string formation and fragmentation to thermalization and jet production, lie largely beyond the reach of standard Euclidean Monte Carlo methods. Hamiltonian formulations of lattice gauge theories, combined with tools from quantum information science, offer a complementary route that provides direct access to time evolution, avoids...