8,779 research outputs found
Quantum Speed Limit for Perfect State Transfer in One Dimension
The basic idea of spin chain engineering for perfect quantum state transfer
(QST) is to find a set of coupling constants in the Hamiltonian, such that a
particular state initially encoded on one site will evolve freely to the
opposite site without any dynamical controls. The minimal possible evolution
time represents a speed limit for QST. We prove that the optimal solution is
the one simulating the precession of a spin in a static magnetic field. We also
argue that, at least for solid-state systems where interactions are local, it
is more realistic to characterize the computation power by the couplings than
the initial energy.Comment: 5 pages, no figure; improved versio
Design and Validation of a Novel and Cost-Effective Animal Tissue Model for Training Laparoscopic Adhesiolysis and Mesh Repair of an Incisional Hernia
Approaching Capacity at High-Rates with Iterative Hard-Decision Decoding
A variety of low-density parity-check (LDPC) ensembles have now been observed
to approach capacity with message-passing decoding. However, all of them use
soft (i.e., non-binary) messages and a posteriori probability (APP) decoding of
their component codes. In this paper, we show that one can approach capacity at
high rates using iterative hard-decision decoding (HDD) of generalized product
codes. Specifically, a class of spatially-coupled GLDPC codes with BCH
component codes is considered, and it is observed that, in the high-rate
regime, they can approach capacity under the proposed iterative HDD. These
codes can be seen as generalized product codes and are closely related to
braided block codes. An iterative HDD algorithm is proposed that enables one to
analyze the performance of these codes via density evolution (DE).Comment: 22 pages, this version accepted to the IEEE Transactions on
Information Theor
Role of interference in quantum state transfer through spin chains
We examine the role that interference plays in quantum state transfer through
several types of finite spin chains, including chains with isotropic Heisenberg
interaction between nearest neighbors, chains with reduced coupling constants
to the spins at the end of the chain, and chains with anisotropic coupling
constants. We evaluate quantitatively both the interference corresponding to
the propagation of the entire chain, and the interference in the effective
propagation of the first and last spins only, treating the rest of the chain as
black box. We show that perfect quantum state transfer is possible without
quantum interference, and provide evidence that the spin chains examined
realize interference-free quantum state transfer to a good approximation.Comment: 10 figure
A Simple Proof of Maxwell Saturation for Coupled Scalar Recursions
Low-density parity-check (LDPC) convolutional codes (or spatially-coupled
codes) were recently shown to approach capacity on the binary erasure channel
(BEC) and binary-input memoryless symmetric channels. The mechanism behind this
spectacular performance is now called threshold saturation via spatial
coupling. This new phenomenon is characterized by the belief-propagation
threshold of the spatially-coupled ensemble increasing to an intrinsic noise
threshold defined by the uncoupled system. In this paper, we present a simple
proof of threshold saturation that applies to a wide class of coupled scalar
recursions. Our approach is based on constructing potential functions for both
the coupled and uncoupled recursions. Our results actually show that the fixed
point of the coupled recursion is essentially determined by the minimum of the
uncoupled potential function and we refer to this phenomenon as Maxwell
saturation. A variety of examples are considered including the
density-evolution equations for: irregular LDPC codes on the BEC, irregular
low-density generator matrix codes on the BEC, a class of generalized LDPC
codes with BCH component codes, the joint iterative decoding of LDPC codes on
intersymbol-interference channels with erasure noise, and the compressed
sensing of random vectors with i.i.d. components.Comment: This article is an extended journal version of arXiv:1204.5703 and
has now been accepted to the IEEE Transactions on Information Theory. This
version adds additional explanation for some details and also corrects a
number of small typo
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