In this work, we study the correlation between entanglement and the negative sign problem in quantum Monte Carlo for the simulation of low-dimensional strongly correlated quantum many body systems. Entanglement entropy characterizes the difficulty of many-body simulation with tensor network state related methods, while the average sign measures the difficulty in many-body simulation for a variety of quantum Monte Carlo methods. Although there exist cases where one type of method works better than the other, it is desirable to find the possible correlation between entanglement and average sign for general hard strongly correlated systems regarding computational complexity. We take the doped two-dimensional Hubbard model as an example and numerically calculate the doping evolution of both the entanglement in the ground state with Density Matrix Renormalization Group and the average sign in the Auxiliary Field Quantum Monte Carlo simulation at low temperature. The results show that they are indeed correlated. The entanglement entropy (average sign) shows a peak (dip) around 20% doping, indicating that it is the difficult region for both methods. The vicinity of 20% doping is also the most intriguing region in both the Hubbard model and cuprate high-Tc superconductors where competing states with close energy intertwine with each other. Recognizing the correlation between entanglement and average sign provides new insight into our understanding of the difficulty in the simulation of strongly correlated quantum many-body systems.
In this work, we study the correlation between entanglement and the negative sign problem in quantum Monte Carlo for the simulation of low-dimensional strongly correlated quantum many body systems. Entanglement entropy characterizes the difficulty of many-body simulation with tensor network state related methods, while the average sign measures the difficulty in many-body simulation for a variety of quantum Monte Carlo methods. Although there exist cases where one type of method works better than the other, it is desirable to find the possible correlation between entanglement and average sign for general hard strongly correlated systems regarding computational complexity. We take the doped two-dimensional Hubbard model as an example and numerically calculate the doping evolution of both the entanglement in the ground state with Density Matrix Renormalization Group and the average sign in the Auxiliary Field Quantum Monte Carlo simulation at low temperature. The results show that they are indeed correlated. The entanglement entropy (average sign) shows a peak (dip) around 20% doping, indicating that it is the difficult region for both methods. The vicinity of 20% doping is also the most intriguing region in both the Hubbard model and cuprate high-Tc superconductors where competing states with close energy intertwine with each other. Recognizing the correlation between entanglement and average sign provides new insight into our understanding of the difficulty in the simulation of strongly correlated quantum many-body systems.
Understanding strongly correlated electrons is an important long-term goal, not only for uncovering fundamental physics behind, but also for their emergence of lots of novel states which have potential applications in quantum control and quantum computations. Meanwhile, the strongly correlated electrons are usually extremely hard problems, and it is generally impossible to understand them unbiasedly. Quantum Monte Carlo is a typical unbiased numeric method, which does not depend on any perturbation, and it can help us to exactly understand the strongly correlated electrons, so that it is widely used in high energy and condensed matter physics. However, quantum Monte Carlo usually suffers from the notorious sign problem. In this paper, we introduce general ideas to design sign problem free models and discuss the sign bound theory we proposed recently. In the sign bound theory, we build a direct connection between the average sign and the ground state properties of the system. We find usually the average sign has the conventional exponential decay with system size increasing, leading to exponential complexity; but for some cases it can have algebraic decay, so that quantum Monte Carlo simulation still has polynomial complexity. By designing sign problem free or algebraic sign behaved strongly correlated electron models, we can approach to several long outstanding problems, such as the itinerant quantum criticality, the competition between unconventional superconductivity and magnetism, as well as the recently found correlated phases and phase transitions in moiré quantum matter.
Quantum simulations are a powerful tool for exploring strongly correlated many-body phenomena. Yet, their reach is limited by the fermion sign problem, which causes configuration weights to become negative, compromising statistical sampling. In auxiliary-field Quantum Monte Carlo calculations of the doped Hubbard model, neglecting the sign S of the weight leads to qualitatively wrong results -- most notably, an apparent suppression rather than enhancement of d-wave pairing at low temperature. Here we approach the problem from a different perspective: instead of identifying negative-weight paths, we examine the statistics of measured observables in a sign-resolved manner. By analyzing histograms of key quantities (kinetic energy, antiferromagnetic structure factor, and pair susceptibilities) for configurations with S=±1, we derive an exact relation linking the bias from ignoring the sign to the difference between sign-resolved means, Δμ, and the average sign, ⟨S⟩. Our framework provides a precise diagnostic of the origin of measurement bias in Quantum Monte Carlo and clarifies why observables such as the d-wave susceptibility are especially sensitive to the sign problem.
We have a strong interest in the interplay between geometrical frustrations and quantum fluctuations in the strongly correlated matter because it causes the emergence of new exotic quantum phases. For example, in the past decade, we have found a number of new Mott insulator materials on a triangular layer: Cs2CuCl4 [1] and organic charge transfer salts [2], such as κ-(BEDT-TTF)2 X and β-Z[Pd(dmit)2]2. There are geometrical frustrations and quantum fluctuations in these materials. Probably, the interplay has an important role for the disordered behaviors at very low temperatures in some materials. In order to study the low temperature property of strongly correlated matter in low-dimensional systems, we need a theoretical tool beyond the mean-field theory. The numerical approach is a candidate. Unfortunately, there are serious drawbacks in the conventional numerical methods. For example, quantum Monte Carlo (QMC) methods are powerful tools because they are unbiased. However, the weight of QMC samples can be negative in quantum frustrated magnets, leading to a cancellation in sign, and the accuracy of simulations fatally decreases (this is the so-called negative sign problem.) Exact diagonalization gives us the detail of a ground state, but it can only be applied to small systems. On the other hand, the variational method is flexible, and it is powerful if we choose the appropriate variational wave function. In the past decade, based on the study of entanglement, we discussed the new types of wave functions for quantum many-body systems. We define the probability amplitudes of these wave functions by the tensor contractions of small tensors. Since the tensor contractions can be drawn as a network, it is called a tensor network state. In this paper, we will report the performance of tensor network state for the variational study of quantum frustrated magnets. There are two major tensor network states: projected entangled pair state(PEPS) [3] and multiscale entanglement renormalization ansatz(MERA) [4]. In the following, we will focus on the MERA, and we will report the performance for S = 1/2 spatially anisotropic triangular antiferromagnets [5]. We organize this paper as follows: In Sec. 2, we will briefly introduce the tensor network. In addition, we will explain a MERA tensor network for triangular lattice models in detail. In Sec. 3, we will show the performance of MERA for the S = 1/2 antiferromagnetic Heisenberg model on a
Quantum Monte Carlo simulations of fermions are hampered by the notorious sign problem whose most striking manifestation is an exponential growth of sampling errors with the number of particles. With the sign problem known to be an NP-hard problem and any generic solution thus highly elusive, the Monte Carlo sampling of interacting many-fermion systems is commonly thought to be restricted to a small class of model systems for which a sign-free basis has been identified. Here we demonstrate that entanglement measures, in particular the so-called R\'enyi entropies, can intrinsically exhibit a certain robustness against the sign problem in auxiliary-field quantum Monte Carlo approaches and possibly allow for the identification of global ground-state properties via their scaling behavior even in the presence of a strong sign problem. We corroborate these findings via numerical simulations of fermionic quantum phase transitions of spinless fermions on the honeycomb lattice at and below half filling.
A, by now, well-known signal-to-noise problem plagues Monte Carlo calculations of quantum-information-theoretic observables in systems of interacting fermions, particularly the Renyi entanglement entropies Sn, even in many cases where the infamous sign problem does not appear. Several methods have been put forward to circumvent this affliction including ensemble-switching techniques using auxiliary partition-function ratios. This dissertation presents an algorithm that modifies the recently proposed free-fermion decomposition in an essential way: we incorporate the entanglement-sensitive correlations directly into the probability measure in a natural way. Implementing this algorithm, we demonstrate that it is compatible with the hybrid Monte Carlo algorithm, the workhorse of the lattice quantum chromodynamics community and an essential tool for studying gauge theories that contain dynamical fermions. By studying a simple one-dimensional Hubbard model, we demonstrate that our method does not exhibit the same debilitating numerical difficulties that naive attempts to study entanglement often encounter. Following that, we illustrate some key probabilistic insights, using intuition derived from the previous method and its successes to construct a simpler, better behaved, and more elegant algorithm. Using this method, in combination with new identities which allow us to avoid seemingly necessary numerical difficulties, the inversion of the restricted one-body density matrices, we compute high order Renyi entropies and perform a thorough comparison to this new algorithm's predecessor using the Hubbard model mentioned before. Finally, we characterize non-perturbatively the Renyi entropies of degree n=2,3,4, and 5 of three-dimensional, strongly coupled many-fermion systems in the scale-invariant regime of short interaction range and large scattering length, i.e. in the unitary limit using the algorithms detailed herein. We also detail an exact, few-body projective method which we use to characterize the entanglement properties of the two-body sector across a broad range of attractive couplings. In the many-body case, we determine universal scaling properties of this system, and for the two-body case, we compute the entanglement spectrum exactly, successfully characterizing a vast range of entanglement behavior across the BCS-BEC crossover.
We introduce the adiabatic quantum Monte Carlo (AQMC) method, where we gradually crank up the interaction strength, as an amelioration of the sign problem. It is motivated by the adiabatic theorem and will approach the true ground state if the evolution time is long enough. We demonstrate that the AQMC algorithm enhances the average sign exponentially such that low enough temperatures can be accessed and ground-state properties probed. It is a controlled approximation that satisfies the variational theorem and provides an upper bound for the ground-state energy. We first benchmark the AQMC algorithm vis-à-vis the undoped Hubbard model on the square lattice which is known to be sign-problem-free within the conventional quantum Monte Carlo formalism. Next, we test the AQMC algorithm against the density-matrix-renormalization-group approach for the doped four-leg ladder Hubbard model and demonstrate its remarkable accuracy. As a nontrivial example, we apply our method to the Hubbard model at p=1/8 doping for a 16×8 system and discuss its ground-state properties. We finally utilize our method and demonstrate the emergence of U(1)_{2}∼SU(2)_{1} topological order in a strongly correlated Chern insulator.