14 research outputs found
Simulation of two-dimensional quantum systems using a tree tensor network that exploits the entropic area law
This work explores the use of a tree tensor network ansatz to simulate the
ground state of a local Hamiltonian on a two-dimensional lattice. By exploiting
the entropic area law, the tree tensor network ansatz seems to produce
quasi-exact results in systems with sizes well beyond the reach of exact
diagonalisation techniques. We describe an algorithm to approximate the ground
state of a local Hamiltonian on a L times L lattice with the topology of a
torus. Accurate results are obtained for L={4,6,8}, whereas approximate results
are obtained for larger lattices. As an application of the approach, we analyse
the scaling of the ground state entanglement entropy at the quantum critical
point of the model. We confirm the presence of a positive additive constant to
the area law for half a torus. We also find a logarithmic additive correction
to the entropic area law for a square block. The single copy entanglement for
half a torus reveals similar corrections to the area law with a further term
proportional to 1/L.Comment: Major rewrite, new version published in Phys. Rev. B with highly
improved numerical results for the scaling of the entropies and several new
sections. The manuscript has now 19 pages and 30 Figure
Boundary quantum critical phenomena with entanglement renormalization
We extend the formalism of entanglement renormalization to the study of
boundary critical phenomena. The multi-scale entanglement renormalization
ansatz (MERA), in its scale invariant version, offers a very compact
approximation to quantum critical ground states. Here we show that, by adding a
boundary to the scale invariant MERA, an accurate approximation to the critical
ground state of an infinite chain with a boundary is obtained, from which one
can extract boundary scaling operators and their scaling dimensions. Our
construction, valid for arbitrary critical systems, produces an effective chain
with explicit separation of energy scales that relates to Wilson's RG
formulation of the Kondo problem. We test the approach by studying the quantum
critical Ising model with free and fixed boundary conditions.Comment: 8 pages, 12 figures, for a related work see arXiv:0912.289
Entanglement renormalization and boundary critical phenomena
The multiscale entanglement renormalization ansatz is applied to the study of
boundary critical phenomena. We compute averages of local operators as a
function of the distance from the boundary and the surface contribution to the
ground state energy. Furthermore, assuming a uniform tensor structure, we show
that the multiscale entanglement renormalization ansatz implies an exact
relation between bulk and boundary critical exponents known to exist for
boundary critical systems.Comment: 6 pages, 4 figures; for a related work see arXiv:0912.164
Tensor network states and geometry
Tensor network states are used to approximate ground states of local
Hamiltonians on a lattice in D spatial dimensions. Different types of tensor
network states can be seen to generate different geometries. Matrix product
states (MPS) in D=1 dimensions, as well as projected entangled pair states
(PEPS) in D>1 dimensions, reproduce the D-dimensional physical geometry of the
lattice model; in contrast, the multi-scale entanglement renormalization ansatz
(MERA) generates a (D+1)-dimensional holographic geometry. Here we focus on
homogeneous tensor networks, where all the tensors in the network are copies of
the same tensor, and argue that certain structural properties of the resulting
many-body states are preconditioned by the geometry of the tensor network and
are therefore largely independent of the choice of variational parameters.
Indeed, the asymptotic decay of correlations in homogeneous MPS and MERA for
D=1 systems is seen to be determined by the structure of geodesics in the
physical and holographic geometries, respectively; whereas the asymptotic
scaling of entanglement entropy is seen to always obey a simple boundary law --
that is, again in the relevant geometry. This geometrical interpretation offers
a simple and unifying framework to understand the structural properties of, and
helps clarify the relation between, different tensor network states. In
addition, it has recently motivated the branching MERA, a generalization of the
MERA capable of reproducing violations of the entropic boundary law in D>1
dimensions.Comment: 18 pages, 18 figure
Efficient quantum state tomography
Quantum state tomography, the ability to deduce the state of a quantum system
from measured data, is the gold standard for verification and benchmarking of
quantum devices. It has been realized in systems with few components, but for
larger systems it becomes infeasible because the number of quantum measurements
and the amount of computation required to process them grows exponentially in
the system size. Here we show that we can do exponentially better than direct
state tomography for a wide range of quantum states, in particular those that
are well approximated by a matrix product state ansatz. We present two schemes
for tomography in 1-D quantum systems and touch on generalizations. One scheme
requires unitary operations on a constant number of subsystems, while the other
requires only local measurements together with more elaborate post-processing.
Both schemes rely only on a linear number of experimental operations and
classical postprocessing that is polynomial in the system size. A further
strength of the methods is that the accuracy of the reconstructed states can be
rigorously certified without any a priori assumptions.Comment: 9 pages, 4 figures. Combines many of the results in arXiv:1002.3780,
arXiv:1002.3839, and arXiv:1002.4632 into one unified expositio
Concatenated tensor network states
We introduce the concept of concatenated tensor networks to efficiently
describe quantum states. We show that the corresponding concatenated tensor
network states can efficiently describe time evolution and possess arbitrary
block-wise entanglement and long-ranged correlations. We illustrate the
approach for the enhancement of matrix product states, i.e. 1D tensor networks,
where we replace each of the matrices of the original matrix product state with
another 1D tensor network. This procedure yields a 2D tensor network, which
includes -- already for tensor dimension two -- all states that can be prepared
by circuits of polynomially many (possibly non-unitary) two-qubit quantum
operations, as well as states resulting from time evolution with respect to
Hamiltonians with short-ranged interactions. We investigate the possibility to
efficiently extract information from these states, which serves as the basic
step in a variational optimization procedure. To this aim we utilize known
exact and approximate methods for 2D tensor networks and demonstrate some
improvements thereof, which are also applicable e.g. in the context of 2D
projected entangled pair states. We generalize the approach to higher
dimensional- and tree tensor networks.Comment: 16 pages, 4 figure
Can One Trust Quantum Simulators?
Various fundamental phenomena of strongly-correlated quantum systems such as
high- superconductivity, the fractional quantum-Hall effect, and quark
confinement are still awaiting a universally accepted explanation. The main
obstacle is the computational complexity of solving even the most simplified
theoretical models that are designed to capture the relevant quantum
correlations of the many-body system of interest. In his seminal 1982 paper
[Int. J. Theor. Phys. 21, 467], Richard Feynman suggested that such models
might be solved by "simulation" with a new type of computer whose constituent
parts are effectively governed by a desired quantum many-body dynamics.
Measurements on this engineered machine, now known as a "quantum simulator,"
would reveal some unknown or difficult to compute properties of a model of
interest. We argue that a useful quantum simulator must satisfy four
conditions: relevance, controllability, reliability, and efficiency. We review
the current state of the art of digital and analog quantum simulators. Whereas
so far the majority of the focus, both theoretically and experimentally, has
been on controllability of relevant models, we emphasize here the need for a
careful analysis of reliability and efficiency in the presence of
imperfections. We discuss how disorder and noise can impact these conditions,
and illustrate our concerns with novel numerical simulations of a paradigmatic
example: a disordered quantum spin chain governed by the Ising model in a
transverse magnetic field. We find that disorder can decrease the reliability
of an analog quantum simulator of this model, although large errors in local
observables are introduced only for strong levels of disorder. We conclude that
the answer to the question "Can we trust quantum simulators?" is... to some
extent.Comment: 20 pages. Minor changes with respect to version 2 (some additional
explanations, added references...