TSCM group @UniTs

Strongly-correlated lattice models

Modern condensed matter is concerned with situations where quantum physics and many-body interactions play a key role to create new physical phenomena.

For most of the last century, low-temperature condensed-matter physics was dominated by the spontaneous-symmetry breaking (Landau) paradigm: at low temperatures, matter reorganises in long-range ordered phases breaking a symmetry of the microscopic Hamiltonian, witnessed by local order parameters. By now, there is a clear evidence that several systems may go beyond this standard description, hosting low-temperature phases characterized by non-trival topological properties, or unconventional quasiparticle excitations, which carry only a fraction of the original degrees of freedom. Such topological phases are robust with respect to perturbations, since they are related to the presence of entaglement stored in the entire system. Examples include Mott insulators, spin liquids, and topological phases.

Our current efforts are devoted to the identification of spin-liquid phases with gapless excitations or topological degeneracy in Mott insulators with magnetic frustration. We are also interested in superconducting phases emerging from strong electron-electron correlations in d orbitals. The paradigmatic example is given by the long-standing high-temperature superconductivity in Copper-oxide materials. In this regard, orbital fluctuations may also drive to unconventional phases, with both topological and superconducting properties that are far from being fully understood. By using numerical techniques (mainly quantum Monte Carlo and exact diagonalizations), we investigate the ground-state and low-energy properties of Hubbard and Heisenberg models (including multi-orbital or multi-flavor cases) on the lattice. Calculations are relevant for a number of materials with unconventional low-temperature properties. Our recent activity (with L. Viteritti) is also focused to understand how machine-learining approaches may be used to describe many-body wave functions in frustrated spin models in low spatial dimensions.

Investigators:

Federico Becca

Soft matter

When the typical size of the elementary constituents becomes mesoscopic, materials become soft: when subject to deformation, they flow more easily than hard matter made of atoms and molecules.

Colloidal suspensions are a prototypical example of soft condensed matter: they are composed by large macromolecules suspended in a microscopic solvent made of smaller molecules. From a fundamental viewpoint, colloids are ideal model systems because of the possibility to tailor their mutual interactions, for instance by controlling their internal architecture or by altering the solvent properties. Understanding the link between these physical parameters and phase behavior or self-assembly is one of the most challenging goals of soft condensed matter physics.

We develop computational models based on effective interactions, which allows one to describe a variety of macromolecular assemblies. We also extend classical approaches to the theory of liquids (such as RHNC-type integral equations) to include the short-range anisotropic interactions (Kern and Frenkel model), in collaboration with A. Giacometti (Padua), F. Lado (NC State University) and F. Sciortino (Rome).

Investigators:

Supercooled liquids and glasses

The theoretical description of the glass transition is one of the main open problems in condensed matter physics. Why does the viscosity of supercooled liquids increase dramatically by decreasing temperature?

Why are some liquids good glass-formers and do not crystallize when supercooled, while others not? What is the origin of the strong dynamical correlations that characterize the motions of atoms and molecules close to the glass transition? To answer these questions, several theories have been developed but none of them provides yet a fully satisfactory, quantitative description.

We use molecular dynamics and Monte Carlo simulations of simple and yet realistic models to ask crucial questions to theories. However, the time scales accessible to conventional simulations are too limited to study the dynamics of supercooled liquids close to the glass transition: even if we employ high performance computing (HPC) resources, simulating one second of the microscopic dynamics of a liquid would require several centuries of wall clock time. One of our goals is to develop efficient simulation methods and fill the colossal gap between the time scales accessible to simulations and experiments. Using the swap Monte Carlo method we accelerated the simulation of glassy colloidal suspensions by several billions of times and measured their structure and thermodynamics under extreme supercooling conditions. We also develop leight-weight but realistic force-fields to simulate supercooled liquids and glasses. We analyze their structure, dynamics and glass-forming ability using statistical physics and machine learning methods. In the long term, our efforts aim at identifying the correct theoretical description of the glass transition.

Investigators:

Electronic structure of materials

We are involved in experiments making massive use of atomic-scale numerical simulations of materials using a first-principles approach.

Nowadays, these simulations are not only an essential key for interpreting experimental results; thanks to their increasingly reliable predictive power, they are also of great help to technology for predicting the properties of materials and of physical/chemical processes, in the phases leading to the design of new materials or new processes. The systems studied are mainly: interfaces, surfaces, hetero- and nanostructures; semiconductors; semi-metals for spintronic applications; metallic surfaces, adsorbates, heterogeneous catalysis.

At the same time, important work is being done on developing new theories and models, as well as algorithms for an operative definition of some important properties and features of systems: piezoelectricity, ferroelectricity, flexoelectricity, theory of the insulating state, theory of polarization, theory of orbital magnetization. For some subjects, such as, for instance, surface physics and heterogeneous catalysis, there is a strong collaboration with experimental groups, and in particular also of this Department and other local research institutions.

Investigators:

Maria Peressi

Ultracold quantum matter

We study quantum properties in many-body physics that give rise to collective excitations and phenomena, and are responsible for the emergence of states such as superconductivity and superfluidity.

Quantum impurities problems — Research on neutral impurities in quantum gases focuses on studying the behavior and effects of non-charged particles (neutral impurities) within ultra-cold atomic or molecular gases. These impurities are typically introduced into the quantum gas, and their interactions with the surrounding atoms or molecules are investigated. The study of neutral impurities in quantum gases has provided valuable insights into various physical phenomena, including quantum dynamics, quantum phase transitions, and many-body physics. This research is significant for understanding fundamental aspects of quantum systems and has potential applications in quantum computing, quantum simulation, and precision measurements.

Exotic states of matter — Quantum droplets and superfluid solids, also known as supersolids, are fascinating phenomena observed in ultracold quantum gases. Quantum droplets are stable, self-bound entities formed by interactions between particles in a gas. Unlike traditional droplets, which are held together by surface tension, quantum droplets arise due to quantum fluctuations and repulsive interparticle interactions. These droplets exhibit unique properties such as density profiles that are spatially localized, effectively behaving as a macroscopic quantum object. On the other hand, supersolids are intriguing states of matter that combine characteristics of both solids and superfluids. In supersolids, atoms arrange in a crystal-like lattice while simultaneously flowing as a superfluid. These exotic states emerge when the repulsive interactions between atoms are balanced with quantum fluctuations, resulting in simultaneous long-range order and coherence. The study of quantum droplets and supersolids in ultracold quantum gases offers valuable insights into the fundamental nature of matter and opens up possibilities for exploring novel quantum phenomena and potential applications in quantum technologies.

Atom-ion Hybrid systems — Atom-ion systems in ultracold gases provide a unique platform for studying a wide range of intriguing phenomena in quantum physics. One fascinating aspect is the formation of ion Bose polaron and ion Fermi polaron complexes. In an ion Bose polaron, an impurity ion interacts with a surrounding gas of bosonic atoms. The strong attractive interaction between the ion and the bosons leads to the dressing of the ion by the bosonic cloud, effectively forming a quasiparticle. This dressing modifies the properties of the ion, such as its mass and spectral features, creating a novel hybrid state. Similarly, in an ion Fermi polaron, the impurity ion interacts with a gas of fermionic atoms. Due to the Pauli exclusion principle, the dressing effect is different compared to the Bose polaron case, resulting in distinct behaviors and characteristics. These atom-ion systems with ultracold gases offer rich opportunities for studying the physics of polaron formation, many-body interactions, and quantum impurity effects, contributing to our understanding of strongly correlated systems and opening up avenues for potential applications in quantum simulation and information processing.

Investigators:

Luis Peña Ardila

People

Permanent members

Federico Becca

Associate professor

Daniele Coslovich

Associate professor

Giorgio Pastore

Associate professor

Maria Peressi

Full professor

Luis Peña Ardila

Tenure-track associate professor

Enrico Smargiassi

Researcher

Students and postdocs

Nicolas Bau

Ph.D. student

Davide Bidoggia

Ph.D. student

Marco Dirindin

Ph.D. student

Mitra Dowlatabadi

Ph.D. student

Roberta Favata

Ph.D. student

Leonardo Galliano

Ph.D. student

Nataliia Manko

Postdoc

Michele Matteucci

Ph.D. student

Francesco Tognocchi

Ph.D. student

Special guests

CM cluster

Our small dedicated CPU cluster, ideal for internship and PhD projects (94 cores, 240 RAM)

Bora cluster

HPC cluster of the Physics Department, funded by the Department of Excellence grant (2023-2028).

Recent publications

"Insulating and metallic phases in the one-dimensional Hubbard-Su-Schrieffer-Heeger model: Insights from a backflow-inspired variational wave function"
Davide Piccioni, Francesco Ferrari, Michele Fabrizio, Federico Becca
Phys. Rev. B 111, 045125 (2025)

The interplay between electron-electron and electron-phonon interactions is studied in a one-dimensional lattice model, by means of a variational Monte Carlo method based on generalized Jastrow-Slater wave functions. Here, the fermionic part is constructed by a pair-product state, which explicitly depends on the phonon configuration, thus including the electron-phonon coupling in a backflow-inspired way. We report the results for the Hubbard model in presence of the Su-Schrieffer-Heeger coupling to optical phonons, both at half-filling and upon hole doping. At half-filling, the ground state is either a translationally invariant Mott insulator, with gapless spin excitations, or a Peierls insulator, which breaks translations and has fully gapped excitations. Away from half-filling, the charge gap closes in both Mott and Peierls insulators, turning the former into a conventional Luttinger liquid (gapless in all excitation channels). The latter, instead, retains a finite spin gap that closes only above a threshold value of the doping. Even though consistent with the general theory of interacting electrons in one dimension, the existence of such a phase (with gapless charge but gapped spin excitations) has never been demonstrated in a model with repulsive interaction and with only two Fermi points. Since the spin-gapped metal represents the one-dimensional counterpart of a superconductor, our results furnish evidence that a true off-diagonal long-range order may exist in the two-dimensional case.
"Glassy dynamics and crystalline local order in two-dimensional amorphous silica"
Marco Dirindin, Daniele Coslovich
J. Phys. Chem. B 129, 1095 (2025)

We reassess the modeling of amorphous silica bilayers as a two-dimensional classical system whose particles interact with an effective pairwise potential. We show that it is possible to reparameterize the potential developed by Roy, Heyde, and Heuer to quantitatively match the structural details of the experimental samples. We then study the glassy dynamics of the reparameterized model at low temperatures. Using appropriate cage-relative correlation functions, which suppress the effect of Mermin-Wagner fluctuations, we highlight the presence of two well-defined Arrhenius regimes separated by a narrow crossover region, which we connect to the thermodynamic anomalies and the changes in the local structure. We find that the bond-orientational order grows steadily below the crossover temperature and is associated to transient crystalline domains of nanometric size. These findings raise fundamental questions about the nature of glass structure in two dimensions and provide guidelines to interpret the experimental data.
"Freezing, melting and the onset of glassiness in binary mixtures"
Daniele Coslovich, Leonardo Galliano, Lorenzo Costigliola
J. Chem. Phys. 162, 061102 (2025)

We clarify the relationship between freezing, melting, and the onset of glassy dynamics in a prototypical glass-forming mixture model. Our starting point is a precise operational definition of the onset of glassiness, as expressed by the emergence of inflections in time-dependent correlation functions. By scanning the temperature-composition phase diagram of the mixture, we find a disconnect between the onset of glassiness and freezing. Surprisingly, however, the onset temperature closely tracks the melting line, along which the excess entropy is approximately constant. At fixed composition, all characteristic temperatures display nonetheless similar pressure dependencies, which are very well predicted by the isomorph theory. While our results rule out a general connection between thermodynamic metastability and glassiness, they call for a reassessment of the role of crystalline precursors in glass-forming liquids.
"Roadmap on machine learning glassy dynamics"
Gerhard Jung, Rinske M. Alkemade, Victor Bapst, Daniele Coslovich, Laura Filion et al.
Nat. Rev. Phys. 7, 91 (2025)

Unraveling the connections between microscopic structure, emergent physical properties, and slow dynamics has long been a challenge when studying the glass transition. The absence of clear visible structural order in amorphous configurations complicates the identification of the key physical mechanisms underpinning slow dynamics. The difficulty in sampling equilibrated configurations at low temperatures hampers thorough numerical and theoretical investigations. This perspective article explores the potential of machine learning (ML) techniques to face these challenges, building on the algorithms that have revolutionized computer vision and image recognition. We present recent successful ML applications, as well as many open problems for the future, such as transferability and interpretability of ML approaches. We highlight new ideas and directions in which ML could provide breakthroughs to better understand the fundamental mechanisms at play in glass-forming liquids. To foster a collaborative community effort, this article also introduces the ``GlassBench" dataset, providing simulation data and benchmarks for both two-dimensional and three-dimensional glass-formers. We propose critical metrics to compare the performance of emerging ML methodologies, in line with benchmarking practices in image and text recognition. The goal of this roadmap is to provide guidelines for the development of ML techniques in systems displaying slow dynamics, while inspiring new directions to improve our theoretical understanding of glassy liquids.
"Spin-phonon interactions on the kagome lattice: Dirac spin liquid versus valence-bond solids"
Francesco Ferrari, Federico Becca, Roser Valenti
Phys. Rev. B 109, 165133 (2024)

We investigate the impact of the spin-phonon coupling on the S=1/2 Heisenberg model on the kagome lattice. For the pure spin model, there is increasing evidence that the low-energy properties can be correctly described by a Dirac spin liquid, in which spinons with a conical dispersion are coupled to emergent gauge fields. Within this scenario, the ground-state wave function is well approximated by a Gutzwiller-projected fermionic state [Y. Ran, M. Hermele, P.A. Lee, and X.-G. Wen, Phys. Rev. Lett. 98, 117205 (2007)]. However, the existence of U(1) gauge fields may naturally lead to instabilities when small perturbations are included. Since phonons are ubiquitous in real materials, they may play a relevant role in the determination of the actual physical properties of the kagome antiferromagnet. We perform a step forward in this direction, including phonon degrees of freedom (at the quantum level) and applying a variational approach based upon Gutzwiller-projected fermionic Ans\"atze. Our results suggest that the Dirac spin liquid is stable for small spin-phonon couplings, while valence-bond solids are obtained at large couplings. Even though different distortions can be induced by the spin-phonon interaction, the general aspect is that the energy is lowered by maximizing the density of perfect hexagons in the dimerization pattern.
"A simple linear algebra identity to optimize Large-Scale Neural Network Quantum States"
Riccardo Rende, Luciano Loris Viteritti, Lorenzo Bardone, Federico Becca, Sebastian Goldt
Communications Physics 7, 260 (2024)

Neural-network architectures have been increasingly used to represent quantum many-body wave functions. These networks require a large number of variational parameters and are challenging to optimize using traditional methods, as gradient descent. Stochastic Reconfiguration (SR) has been effective with a limited number of parameters, but becomes impractical beyond a few thousand parameters. Here, we leverage a simple linear algebra identity to show that SR can be employed even in the deep learning scenario. We demonstrate the effectiveness of our method by optimizing a Deep Transformer architecture with $3 \times 10^5$ parameters, achieving state-of-the-art ground-state energy in the $J_1$-$J_2$ Heisenberg model at $J_2/J_1=0.5$ on the $10\times10$ square lattice, a challenging benchmark in highly-frustrated magnetism. This work marks a significant step forward in the scalability and efficiency of SR for Neural-Network Quantum States, making them a promising method to investigate unknown quantum phases of matter, where other methods struggle.
"Fine-tuning Neural Network Quantum States"
Riccardo Rende, Sebastian Goldt, Federico Becca, Luciano Loris Viteritti
Phys. Rev. Research 6, 043280 (2024)

Recent progress in the design and optimization of neural-network quantum states (NQSs) has made them an effective method to investigate ground-state properties of quantum many-body systems. In contrast to the standard approach of training a separate NQS from scratch at every point of the phase diagram, we demonstrate that the optimization of a NQS at a highly expressive point of the phase diagram (i.e., close to a phase transition) yields features that can be reused to accurately describe a wide region across the transition. We demonstrate the feasibility of our approach on different systems in one and two dimensions by initially pretraining a NQS at a given point of the phase diagram, followed by fine-tuning only the output layer for all other points. Notably, the computational cost of the fine-tuning step is very low compared to the pretraining stage. We argue that the reduced cost of this paradigm has significant potential to advance the exploration of strongly-correlated systems using NQS, mirroring the success of fine-tuning in machine learning and natural language processing.
"Variational Benchmarks for Quantum Many-Body Problems"
Dian Wu, Riccardo Rossi, Filippo Vicentini, Nikita Astrakhantsev, Federico Becca et al.
Science 386, 296-301 (2024)

The continued development of computational approaches to many-body ground-state problems in physics and chemistry calls for a consistent way to assess its overall progress. In this work, we introduce a metric of variational accuracy, the V-score, obtained from the variational energy and its variance. We provide an extensive curated dataset of variational calculations of many-body quantum systems, identifying cases where state-of-the-art numerical approaches show limited accuracy, and future algorithms or computational platforms, such as quantum computing, could provide improved accuracy. The V-score can be used as a metric to assess the progress of quantum variational methods toward a quantum advantage for ground-state problems, especially in regimes where classical verifiability is impossible.
"Policy-guided Monte Carlo on general state spaces: Application to glass-forming mixtures"
Leonardo Galliano, Riccardo Rende, Daniele Coslovich
J. Chem. Phys. 161, 064503 (2024)

Policy-guided Monte Carlo is an adaptive method to simulate classical interacting systems. It adjusts the proposal distribution of the Metropolis-Hastings algorithm to maximize the sampling efficiency, using a formalism inspired by reinforcement learning. In this work, we first extend the policy-guided method to deal with a general state space, comprising, for instance, both discrete and continuous degrees of freedom, and then apply it to a few paradigmatic models of glass-forming mixtures. We assess the efficiency of a set of physically inspired moves whose proposal distributions are optimized through on-policy learning. Compared to conventional Monte Carlo methods, the optimized proposals are two orders of magnitude faster for an additive soft sphere mixture but yield a much more limited speed-up for the well-studied Kob-Andersen model. We discuss the current limitations of the method and suggest possible ways to improve it.
"Universal properties of dipolar Bose polarons in two dimensions"
Juan Sánchez-Baena, Luis A. Peña Ardila, Grigory Astrakharchik, Ferran Mazzanti
J. S\'anchez-Baena, L. A. Pe\~na Ardila, G. E. Astrakharchik, and F. Mazzanti, Phys. Rev. A 110, 023317 (2024)

We study the quasiparticle properties of a dipolar impurity immersed in a two-dimensional dipolar bath. We use the ab-initio Diffusion Monte Carlo technique to determine the polaron energy, effective mass and quasiparticle residue. We find that both the polaron energy and quasiparticle residue follow a universal behaviour with respect to the polarization angle when properly scaled in terms of the scattering length. This trend is maintained over a wide range of values of the gas parameter, even in the highly correlated regime. Instead, the effective mass shows growing anisotropy as the tilting angle is increased, which is induced, mainly, by the anisotropy of the impurity-boson dipole-dipole interaction. Surprisingly, the effective mass is larger in the direction of minimum inter-particle repulsion. Finally, we use our Monte Carlo results to check the accuracy of perturbative approaches and determine their range of validity in terms of the gas parameter.
"Modified mean field ansatz for charged polarons in a Bose-Einstein condensate"
Ubaldo Cavazos Olivas, Luis A. Peña Ardila, Krzysztof Jachymski
Phys. Rev. A 110, L011301 (2024)

Ionic Bose polarons are quantum entities emerging from the interaction between an ion and a Bose-Einstein condensate (BEC), featuring long-ranged interactions that can compete with the gas healing length. This can result in strong interparticle correlations and enhancement of gas density around the ion. One possible approach to describe this complex system with high accuracy relies on numerical treatment such as the quantum Monte Carlo (QMC) techniques. Nevertheless, it is computationally very expensive and does not easily allow to study the system dynamics. On the other hand, a mean-field based variational ansatz in the co-moving frame can capture a sizeable change in the gas density. We apply it to the case of regularized ion-atom potential and find that it qualitatively reproduces the full numerical results. In addition, we also study the system of two pinned ions, focusing on their effective interaction induced by the bath. This approach seems to be promising for studying transport and nonequilibrium dynamics of charged (bi)polarons in condensed media.

Theory and simulation of condensed matter @UniTS

News

A roadmap on machine learning glassy dynamics published in Nature Reviews Physics

A milestone in solving the quantum many-body problem published in Science

Welcome to Luis Aldemar Peña Ardila!

Our research

Strongly-correlated lattice models

Soft matter

Supercooled liquids and glasses

Electronic structure of materials

Ultracold quantum matter

Join our group

People

Permanent members

Federico Becca

Daniele Coslovich

Giorgio Pastore

Maria Peressi

Luis Peña Ardila

Enrico Smargiassi

Students and postdocs

Nicolas Bau

Davide Bidoggia

Marco Dirindin

Mitra Dowlatabadi

Roberta Favata

Leonardo Galliano

Nataliia Manko

Michele Matteucci

Francesco Tognocchi

Special guests

CM cluster

Bora cluster

Recent publications