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Although the entanglement entropy probing novel phases and phase transitions numerically via quantum Monte Carlo (QMC) has achieved huge success in pure ground states of quantum many-body systems, numerical explorations on mixed states remain limited, despite the fact that most real-world systems are non-isolated. Meanwhile, entanglement negativity, as a rarely computable entanglement monotone for mixed states, is significant in characterizing mixed-state entanglement, such as in systems with two disconnected regions, dissipation or at finite temperature. However, efficient numerical approaches are scarce to calculate this quantity in large-scale and high-dimensional systems, especially when we need to access how it varies with certain parameters to study critical behaviors. Within the reweight-annealing frame, we present an accessible and efficient QMC algorithm, which is able to achieve the values as well as tracking the variation of the R\'enyi version of entanglement negativity on some specified parameter path. Our algorithm makes it feasible to directly study the role that entanglement plays at the critical point and in different phases for mixed states in high dimensions numerically. In addition, this method is accessible and easy to parallelize on computers. Through this method, different intrinsic mechanisms in quantum and thermal criticalities with the same universal class have been revealed clearly through the numerical calculations on R\'enyi negativity., Comment: 10 pages, 4 figures

Using entanglement entropy (EE) to probe the intrinsic physics of the novel phases and phase transitions in quantum many-body systems is an important but challenging topic in condensed matter physics. Thanks to our newly developed bipartite-reweight-annealing algorithm, we can systematically study EE behaviors near both first and second-order phase transition points of two-dimensional strongly correlated systems by scanning the EE across a large parameter region, which was super difficult previously due to the huge computation resources demanded. Interestingly, we find that the EE or its derivative diverges at the critical point, which essentially reveals the phase transition involving discrete or continuous symmetry breaking. What's more, we observe that the peak of the EE curve can detect first-order phase transitions at high symmetry breaking points, separating phases with lower symmetry broken. This behavior also applies to the symmetry-enhanced first-order phase transition in the two-dimensional chequerboard $J-Q$ model, where the emergent higher symmetry arises from the related deconfined criticality beyond the Landau-Ginzburg-Wilson paradigm. This work points to new phenomena and mechanisms that can help us better identify different phase transitions and the underlying symmetry breaking., Comment: 10 pages, 7 figures

We propose a quantum Monte Carlo (QMC) scheme able to extract large-scale data of entanglement entropy (EE) and its derivative with high precision and low technical barrier. We avoid directly computing the overlap of two partition functions within different spacetime manifolds and instead obtain them separately via reweight-annealing scheme. The incremental process can be designed along the path of real physical parameters in this frame, and all intermediates are EEs of corresponding parameters, so the algorithm efficiency is improved by more than $10^4$ of times. The calculation of EE becomes much cheaper and simpler. It opens a way to numerically detect the novel phases and phase transitions by scanning EE in a wide parameter-region in two and higher dimensional systems. We then show the feasibility of using EE and its derivative to find phase transition points and to probe novel phases.

Efficient and accurate algorithm for partition function, free energy and thermal entropy calculations is of great significance in statistical physics and quantum many-body physics. Here we present an unbiased but low-technical-barrier algorithm within the quantum Monte Carlo framework, which has exceptionally high accuracy and no systemic error. Compared with the conventional specific heat integral method and Wang-Landau sampling algorithm, our method can obtain a much more accurate result of the sub-leading coefficient of the entropy. This method can be widely used in both classical and quantum Monte Carlo simulations and is easy to be parallelized on computer., Comment: 10 pages, 7 figures

Low-lying entanglement spectrum provides the quintessential fingerprint to identify the highly entangled quantum matter with topological and conformal field-theoretical properties. However, when the entangling region acquires long boundary with the environment, such as that between long coupled chains or in two or higher dimensions, there unfortunately exists no universal yet practical method to compute the entanglement spectra with affordable computational cost. Here we propose a new scheme to overcome such difficulty and successfully extract the low-lying fine entanglement spectrum (ES). We trace out the environment via quantum Monte Carlo simulation and diagonalize the reduced density matrix to gain the ES. We demonstrate the strength and reliability of our method through long coupled spin chains and answer its long-standing controversy. Our simulation results, with unprecedentedly large system sizes, establish the practical computation scheme of the entanglement spectrum with a huge freedom degree of environment.

Optimization problems are the core challenge in many fields of science and engineering, yet general and effective methods are scarce for searching optimal solutions. Quantum computing has been envisioned to help solve such problems, for example, the quantum annealing (QA) method based on adiabatic evolution has been extensively explored and successfully implemented on quantum simulators such as D-wave's annealers and some Rydberg arrays. In this work, we investigate topological sector optimization (TSO) problem, which attracts particular interests in the quantum many-body physics community. We reveal that the topology induced by frustration in the spin model is an intrinsic obstruction for QA and other traditional methods to approach the ground state. We demonstrate that the optimization difficulties of TSO problem are not restricted to the gaplessness, but are also due to the topological nature which are often ignored for the analysis of optimization problems before. To solve TSO problems, we utilize quantum imaginary time evolution (QITE) with a possible realization on quantum computers, which exploits the property of quantum superposition to explore the full Hilbert space and can thus address optimization problems of topological nature. We report the performance of different quantum optimization algorithms on TSO problems and demonstrate that their capability to address optimization problems are distinct even when considering the quantum computational resources required for practical QITE implementations., Comment: 12 pages, 11 figures

Beyond the Li-Haldane-Poilblanc conjecture, we find the entanglement Hamiltonian (EH) is actually not closely similar to the original Hamiltonian on the virtual edge. Unexpectedly, the EH has some relevant long-range interacting terms which hugely affect the physics. Without loss of generality, we study a spin-1/2 Heisenberg bilayer to obtain the entanglement information between the two layers through our newly developed quantum Monte Carlo scheme, which can simulate large-scale EH. Although the entanglement spectrum carrying the Goldstone mode seems like a Heisenberg model on a single layer, which is consistent with Li-Haldane-Poilblanc conjecture, we demonstrate that there actually exists a finite-temperature phase transition of the EH. The results violate the Mermin-Wagner theorem, which means there should be relevant long-range terms in the EH. It reveals that the Li-Haldane-Poilblanc conjecture ignores necessary corrections for the EH which may lead totally different physics., Comment: 9 pages, 4 figures

Consider piecewise linear Lorenz maps on $[0, 1]$ of the following form \[ f_{a,b,c}(x)= {ll} ax+1-ac & x \in [0, c) b(x-c) & x \in (c, 1].\] We prove that $f_{a,b,c}$ admits an absolutely continuous invariant probability measure (acim) $\mu$ with respect to the Lebesgue measure if and only if $f_{a,b,c}(0) \le f_{a,b,c}(1)$, i.e. $ac+(1-c)b \ge 1$. The acim is unique and ergodic unless $f_{a,b,c}$ is conjugate to a rational rotation. The equivalence between the acim and the Lebesgue measure is also fully investigated via the renormalization theory.

For each piecewise linear Lorenz map that expand on average, we show that it admits a dichotomy: it is either periodic renormalizable or prime. As a result, such a map is conjugate to a $\beta$-transformation., Comment: 18 pages, 1 figure