Hybrid quantum-classical optimization techniques, which incorporate the pre-optimization of Variational Quantum Algorithms (VQAs) using Tensor Networks (TNs), have been shown to allow for the reduction of quantum computational resources. In the particular case of large optimization problems, commonly found in real-world use cases, this strategy is almost mandatory to reduce the otherwise...
We use quantum devices from IBMQ to perform digital quantum simulations of the Schwinger model. We work with a quantum link model description of the Schwinger model in its lowest dimensional representation, and use gauge invariance, in the form of the Gauss' law, to enhance quality of data from quantum simulations. One of our goals in this project is to find out if there are advantages of...
Rydberg tweezer arrays provide a platform for realizing spin-1/2 Hamiltonians with long-range tunnelings decaying according to power-law with the distance. We numerically investigate the effects of positional disorder and dimerization on the properties of excited states in such a one-dimensional system. Our model allows for the continuous tuning of dimerization patterns and disorder strength....
In this presentation, I shall discuss how one can use Symmetric tensors to study theories with local gauge symmetries and how this can be used to study 2+1D Quantum lattice models or two and three dimensional classical gauge theories using Tensor network methods like PEPS or Tensor renormalisation group.
The Heisenberg antiferromagnet on the maple leaf lattice is a recent candidate host for spin liquid phases ([1, 2, 3]) and can also be realized experimentally both in natural minerals ([4, 5]) as well as synthetic compounds ([6, 7]). Employing exact diagonalization we investigate different ground states and map out the phase diagram under variations of three symmetry-inequivalent...
Determining optimal time-dependent fields to steer quantum systems is a critical yet computationally demanding
task, often complicated by vast and complex search landscapes. This work explores the application
of tensor network methodologies to navigate these high-dimensional parameter spaces in quantum optimal
control effectively. We investigate how structured, low-rank tensor...
We introduce a model-independent method to construct Matrix Product Operator (MPO) representations of quasiparticle creation operators acting on the interacting vacuum of (quasi-)one-dimensional quantum many-body systems. This method exploits maximally localized Wannier functions constructed from single-particle states at intermediate system sizes, which provides the building blocks for a...
We study the behavior of magic as a bipartite correlation in the quantum Ising chain across its quantum phase transition, and at finite temperature. In order to quantify the magic of partitions rigorously, we formulate a hybrid scheme that combines stochastic sampling of reduced density matrices via quantum Monte Carlo, with state-of-the-art estimators for the robustness of magic - a *bona...
Using the developed thermal tensor-network approach, we investigate the spin Seebeck effect (SSE) of the triangular-lattice quantum antiferromagnet hosting spin supersolid phase. We focus on the low-temperature scaling behaviors of the normalized spin current across the interface. Using the 1D Heisenberg chain as a benchmark system, we observe a negative spinon spin current exhibiting...
We discuss the string breaking dynamics in the presence of creation of dynamical charge pair. We consider different string configuration that belong to different sectors and their ability to escape a false vacuum. We then further analyze how they set the onset critical time and critical point and local observables and entanglement profile that signal the dynamical quantum phase transition.
The $t$-$J$ model is one of the simplest theoretical models believed to capture key aspects of high-temperature superconductivity in cuprate materials. Despite extensive study, the nature of its ground state at finite doping remains unsettled. Stripe order, characterized by intertwined charge and spin density waves, appears to compete closely with d-wave superconductivity. Previous DMRG...
Projected entangled-pair states (PEPS) have become a powerful tool for studying quantum many-body systems in the condensed matter and quantum materials context, particularly with advances in variational energy optimization methods. A key challenge within this framework is the computational cost associated with the contraction of the two-dimensional lattice, crucial for calculating state vector...
