arXiv subjects

Andrew J. Ferris

Publications and source records attributed to Andrew J. Ferris.

14 recordsLinked to original sources

arXiv2017

Resonator reset in circuit QED by optimal control for large open quantum systems

We study an implementation of the open GRAPE (Gradient Ascent Pulse Engineering) algorithm well suited for large open quantum systems. While typical implementations of optimal control algorithms for open quantum systems rely on explicit matrix exponential calculations, our implementation avoids these operations leading to a polynomial speed-up of the open GRAPE algorithm in cases of interest. This speed-up, as well as the reduced memory requirements of our implementation, are illustrated by comparison to a standard implementation of open GRAPE. As a practical example, we apply this open-system optimization method to active reset of a readout resonator in circuit QED. In this problem, the shape of a microwave pulse is optimized such as to empty the cavity from measurement photons as fast as possible. Using our open GRAPE implementation, we obtain pulse shapes leading to a reset time over four times faster than passive reset.

quant-ph↗

arXiv2016

Chiral oily streaks in a smectic-A liquid crystal

The liquid crystal octylcyanobiphenyl (8CB) was doped with the chiral agent CB15 and spin-coated onto a substrate treated for planar alignment of the director, resulting in a film of thickness several hundred nm in the smectic-A phase. In both doped and undoped samples, the competing boundary conditions - planar alignment at the substrate and vertical alignment at the free surface - cause the liquid crystal to break into a series of flattened hemicylinders to satisfy the boundary conditions. When viewed under an optical microscope with crossed polarizers, this structure results in a series of dark and light stripes ("oily streaks") of period ~ 1 $μ$m. In the absence of chiral dopant the stripes run perpendicular to the substrate's easy axis. However, when doped with chiral CB15 at concentrations up to c = 4 wt-%, the stripe orientation rotates by a temperature-dependent angle $ϕ$ with respect to the c = 0 stripe orientation, where $ϕ$ increases monotonically with c. $ϕ$ is largest just below the nematic -- smectic-A transition temperature TNA and decreases with decreasing temperature. As the temperature is lowered, $ϕ$ relaxes to a steady-state orientation close to zero within ~1$^\circ$ C of TNA. We suggest that the rotation phenomenon is a manifestation of the surface electroclinic effect: The rotation is due to the weak smectic order parameter and resulting large director tilt susceptibility with respect to the smectic layer normal near TNA, in conjunction with an effective surface electric field due to polar interactions between the liquid crystal and substrate.

cond-mat.soft↗

arXiv2016

An efficient perturbation theory of density matrix renormalization group

Density matrix renormalization group (DMRG) is one of the most powerful numerical methods available for many-body systems. In this work, we develop a perturbation theory of DMRG (PT-DMRG) to largely increase its accuracy in an extremely simple and efficient way. By using the canonical matrix product state (MPS) representation for the ground state of the considered system, a set of orthogonal basis functions $\left\lbrace | ψ_i \rangle \right\rbrace$ is introduced to describe the perturbations to the ground state obtained by the conventional DMRG. The Schmidt numbers of the MPS that are beyond the bond dimension cut-off are used to define such perturbation terms. The perturbed Hamiltonian is then defined as $\tilde{H}_{ij}= \langle ψ_i | \hat{H} | ψ_j \rangle$; its ground state permits to calculate physical observables with a considerably improved accuracy as compared to the original DMRG results. We benchmark the second-order perturbation theory with the help of one-dimensional Ising chain in a transverse field and the Heisenberg chain, where the precision of DMRG is shown to be improved $\rm O(10)$ times. Furthermore, for moderate length $L$ the errors of DMRG and PT-DMRG both scale linearly with $L^{-1}$. The linear relation between the dimension cut-off of DMRG and that of PT-DMRG with the same precision shows a considerable improvement of efficiency, especially for large dimension cut-off's. In thermodynamic limit we show that the errors of PT-DMRG scale with $\sqrt{L^{-1}}$. Our work suggests an effective way to define the tangent space of the ground state MPS, which may shed lights on the properties beyond the ground state. Such second-order PT-DMRG can be readily generalized to higher orders, as well as applied to the models in higher dimensions.

cond-mat.str-el↗

arXiv2016

Modified spin-wave theory and spin liquid behavior of cold bosons on an inhomogeneous triangular lattice

Ultracold bosons in a triangular lattice are a promising candidate for observing quantum spin liquid behavior. Here we investigate, for such system, the role of a harmonic trap giving rise to an inhomogeneous density. We construct a modified spin-wave theory for arbitrary filling, and predict the breakdown of order for certain values of the lattice anisotropy. These regimes, identified with the spin liquid phases, are found to be quite robust upon changes in the filling factor. This result is backed by an exact diagonalization study on a small lattice.

cond-mat.quant-gas↗

arXiv2015

Unbiased Monte Carlo for the age of tensor networks

A new unbiased Monte Carlo technique called Tensor Network Monte Carlo (TNMC) is introduced based on sampling all possible renormalizations (or course-grainings) of tensor networks, in this case matrix-product states. Tensor networks are a natural language for expressing a wide range of discrete physical and statistical problems, such as classical and quantum systems on a lattice at thermal equilibrium. By simultaneously sampling multiple degrees of freedom associated with each bond of the tensor network (and its renormalized form), we can achieve unprecedented low levels of statistical fluctuations which simultaneously parallel the impressive accuracy scaling of tensor networks while avoiding completely the variational bias inherent to those techniques, even with small bond dimensions. The resulting technique is essentially an aggressive multi-sampling technique that can account for the great majority of the partition function in a single sample. The method is quite general and can be combined with a variety of tensor renormalization techniques appropriate to different geometries and dimensionalities.

cond-mat.stat-mech↗

arXiv2014

Fourier transform of fermionic systems and the spectral tensor network

Leveraging the decomposability of the fast Fourier transform, I propose a new class of tensor network that is efficiently contractible and able to represent many-body systems with local entanglement that is greater than the area law. Translationally invariant systems of free fermions in arbitrary dimensions as well as 1D systems solved by the Jordan-Wigner transformation are shown to be exactly represented in this class. Further, it is proposed that these tensor networks be used as generic structures to variationally describe more complicated systems, such as interacting fermions. This class shares some similarities with Evenbly & Vidal's branching MERA, but with some important differences and greatly reduced computational demands.

quant-ph↗

arXiv2014

Tensor Networks and Quantum Error Correction

We establish several relations between quantum error correction (QEC) and tensor network (TN) methods of quantum many-body physics. We exhibit correspondences between well-known families of QEC codes and TNs, and demonstrate a formal equivalence between decoding a QEC code and contracting a TN. We build on this equivalence to propose a new family of quantum codes and decoding algorithms that generalize and improve upon quantum polar codes and successive cancellation decoding in a natural way.

quant-ph↗

arXiv2013

Branching MERA codes: a natural extension of polar codes

We introduce a new class of circuits for constructing efficiently decodable error-correction codes, based on a recently discovered contractible tensor network. We perform an in-depth study of a particular example that can be thought of as an extension to Arikan's polar code. Notably, our numerical simulation show that this code polarizes the logical channels more strongly while retaining the log-linear decoding complexity using the successive cancellation decoder. These codes also display improved error-correcting capability with only a minor impact on decoding complexity. Efficient decoding is realized using powerful graphical calculus tools developed in the field of quantum many-body physics. In a companion paper, we generalize our construction to the quantum setting and describe more in-depth the relation between classical and quantum error correction and the graphical calculus of tensor networks.

quant-ph↗

arXiv2013

The area law and real-space renormalization

Real-space renormalization-group techniques for quantum systems can be divided into two basic categories - those capable of representing correlations following a simple boundary (or area) law, and those which are not. I discuss the scaling of the accuracy of gapped systems in the latter case and analyze the resultant spatial anisotropy. It is apparent that particular points in the system, that are somehow `central' in the renormalization, have local quantities that are much closer to the exact results in the thermodynamic limit than the system-wide average. Numerical results from the tree-tensor network and tensor renormalization-group approaches for the 2D transverse-field Ising model and 3D classical Ising model, respectively, clearly demonstrate this effect.

cond-mat.str-el↗

arXiv2012

Algorithms for the Markov Entropy Decomposition

The Markov entropy decomposition (MED) is a recently-proposed, cluster-based simulation method for finite temperature quantum systems with arbitrary geometry. In this paper, we detail numerical algorithms for performing the required steps of the MED, principally solving a minimization problem with a preconditioned Newton's algorithm, as well as how to extract global susceptibilities and thermal responses. We demonstrate the power of the method with the spin-1/2 XXZ model on the 2D square lattice, including the extraction of critical points and details of each phase. Although the method shares some qualitative similarities with exact-diagonalization, we show the MED is both more accurate and significantly more flexible.

cond-mat.stat-mech↗

arXiv2012

Perfect Sampling with Unitary Tensor Networks

Tensor network states are powerful variational ansätze for many-body ground states of quantum lattice models. The use of Monte Carlo sampling techniques in tensor network approaches significantly reduces the cost of tensor contractions, potentially leading to a substantial increase in computational efficiency. Previous proposals are based on a Markov chain Monte Carlo scheme generated by locally updating configurations and, as such, must deal with equilibration and autocorrelation times, which result in a reduction of efficiency. Here we propose a perfect sampling scheme, with vanishing equilibration and autocorrelation times, for unitary tensor networks -- namely tensor networks based on efficiently contractible, unitary quantum circuits, such as unitary versions of the matrix product state (MPS) and tree tensor network (TTN), and the multi-scale entanglement renormalization ansatz (MERA). Configurations are directly sampled according to their probabilities in the wavefunction, without resorting to a Markov chain process. We also describe a partial sampling scheme that can result in a dramatic (basis-dependent) reduction of sampling error.

cond-mat.str-el↗

arXiv2012

Variational Monte Carlo with the Multi-Scale Entanglement Renormalization Ansatz

Monte Carlo sampling techniques have been proposed as a strategy to reduce the computational cost of contractions in tensor network approaches to solving many-body systems. Here we put forward a variational Monte Carlo approach for the multi-scale entanglement renormalization ansatz (MERA), which is a unitary tensor network. Two major adjustments are required compared to previous proposals with non-unitary tensor networks. First, instead of sampling over configurations of the original lattice, made of L sites, we sample over configurations of an effective lattice, which is made of just log(L) sites. Second, the optimization of unitary tensors must account for their unitary character while being robust to statistical noise, which we accomplish with a modified steepest descent method within the set of unitary tensors. We demonstrate the performance of the variational Monte Carlo MERA approach in the relatively simple context of a finite quantum spin chain at criticality, and discuss future, more challenging applications, including two dimensional systems.

cond-mat.str-el↗

arXiv2009

Atomic entanglement generation and detection via degenerate four-wave-mixing of a Bose-Einstein condensate in an optical lattice

The unequivocal detection of entanglement between two distinct matter-wave pulses is a significant challenge that has yet to be experimentally demonstrated. We describe a realistic scheme to generate and detect continuous variable entanglement between two atomic matter-wave pulses produced via degenerate four-wave-mixing from an initially trapped Bose-Einstein condensate loaded into a one-dimensional optical lattice. We perform a comprehensive numerical investigation for fixed condensate parameters to determine the maximum violation of separability and Einstein-Podolsky-Rosen inequalities for field quadrature entanglement, and describe and simulate an experimental scheme for measuring the necessary quadratures.

cond-mat.other↗

arXiv2007

Dynamical instabilities of Bose-Einstein condensates at the band-edge in one-dimensional optical lattices

We report on experiments that demonstrate dynamical instability in a Bose-Einstein condensate at the band-edge of a one-dimensional optical lattice. The instability manifests as rapid depletion of the condensate and conversion to a thermal cloud. We consider the collisional processes that can occur in such a system, and perform numerical modeling of the experiments using both a mean-field and beyond mean-field approach. We compare our numerical results to the experimental data, and find that the Gross-Pitaevskii equation is not able to describe this experiment. Our beyond mean-field approach, known as the truncated Wigner method, allows us to make quantitative predictions for the processes of parametric growth and thermalization that are observed in the laboratory, and we find good agreement with the experimental results.

cond-mat.other↗