arXiv subjects

Darren Pereira

Publications and source records attributed to Darren Pereira.

6 recordsLinked to original sources

arXiv2026

Spin-spiral instability of the Nagaoka ferromagnet in the crossover between square and triangular lattices

We study the hard-core Fermi-Hubbard model in the crossover between square and triangular lattices near half-filling. As was recognized by Nagaoka in the 1960s, on the square lattice the presence of a single hole leads to ferromagnetic spin ordering. On the triangular lattice, geometric frustration instead leads to a spin-singlet ground state, which can be associated with a 120-degree spiral order. On lattices which interpolate between square and triangular, there is a phase transition at which the ferromagnetic order becomes unstable to a spin spiral. We model this transition, finding the exact location of the spin-spiral instability.

cond-mat.str-el↗

arXiv2025

Kinetic magnetism in the crossover between the square and triangular lattice Fermi-Hubbard models

We calculate the spin correlations that result from the motion of a single dopant in the hard-core Fermi-Hubbard model, as the geometry evolves from a square to a triangular lattice. In particular, we consider the square lattice with an additional hopping along one diagonal, whose strength is continuously varied. We use a high-temperature expansion which expresses the partition function as a sum over closed paths taken by the dopant. We sample thousands of diagrams in the space of closed paths using the quantum Monte Carlo approach of Raghavan and Elser [1,2], which is free of finite-size effects and allows us to simulate temperatures as low as $T \sim 0.3|t|$, even in cases where there is a sign problem. For the case of a hole dopant, we find a crossover from kinetic ferromagnetism to kinetic antiferromagnetism as the geometry is tuned from square to triangular, which can be observed in current quantum gas microscopes.

cond-mat.str-el↗

arXiv2025

Efficient tensor-network simulations of weakly-measured quantum circuits

We present a tensor-network-based method for simulating a weakly-measured quantum circuit. In particular, we use a Markov chain to efficiently sample measurements and contract the tensor network, propagating their effect forward along the spatial direction. Applications of our algorithm include validating quantum computers (capable of mid-circuit measurements) in regimes of easy classical simulability, and studying generative-machine-learning applications, where sampling from complex stochastic processes is the main task. As a demonstration of our algorithm, we consider a (1+1)-dimensional brickwall circuit of Haar-random unitaries, interspersed with generalized single-qubit measurements of variable strength. We simulate the dynamics for tens to hundreds of qubits if the circuit exhibits area-law entanglement (under strong measurements), and tens of qubits if it exhibits volume-law entanglement (under weak measurements). We observe signatures of a measurement-induced phase transition between the two regimes as a function of measurement strength.

quant-ph↗

arXiv2024

Dynamics of spin helices in the diluted one-dimensional $XX$ model

Motivated by discrepancies between recent cold atom experiments and the associated theory, we explore the effect of immobile holes on the quantum dynamics of $x$-$z$ spin helices in the one-dimensional $XX$ model. We calculate the exact spin dynamics by mapping onto a system of non-interacting fermions, averaging over the distribution of holes. At small hole densities we find that the helical spin pattern decays exponentially, with a pitch dependence that agrees with the experiments. At large hole densities we instead find persistent oscillations. While our analytic approach does not generalize to the $XXZ$ model with arbitrary anisotropies, we validate a matrix product state technique which might be used to model the experiments in those settings.

cond-mat.quant-gas↗

arXiv2022

Dynamics of Spin Helices in the One-Dimensional $XX$ Model

Motivated by cold-atom experiments and a desire to understand far-from-equilibrium quantum transport, we analytically study the dynamics of spin helices in the one-dimensional $XX$ model. We use a Jordan-Wigner transformation to map the spin chain onto a non-interacting Fermi gas with simple equations of motion. The resulting dynamics are nontrivial, however, as the spin-helix initial condition corresponds to a highly nonequilibrium distribution of the fermions. We find a separation of timescales between the in-plane and out-of-plane spin dynamics. We gain insights from analyzing the case of a uniform spin chain and from a semiclassical model. One of our key findings is that the spin correlation functions decay as $t^{-1/2}$ at long time, in contrast to the experimentally observed exponential decay.

cond-mat.str-el↗

arXiv2020

Unsupervised Machine Learning of Quenched Gauge Symmetries: A Proof-of-Concept Demonstration

In condensed matter physics, one of the goals of machine learning is the classification of phases of matter. The consideration of a system's symmetries can significantly assist the machine in this goal. We demonstrate the ability of an unsupervised machine learning protocol, the Principal Component Analysis method, to detect hidden quenched gauge symmetries introduced via the so-called Mattis gauge transformation. Our work reveals that unsupervised machine learning can identify hidden properties of a model and may therefore provide new insights into the models themselves.

cond-mat.dis-nn↗