Guessing Revisited: A Large Deviations Approach

The problem of guessing a random string is revisited. A close relation between guessing and compression is first established. Then it is shown that if the sequence of distributions of the information spectrum satisfies the large deviation property with a certain rate function, then the limiting guessing exponent exists and is a scalar multiple of the Legendre-Fenchel dual of the rate function. Other sufficient conditions related to certain continuity properties of the information spectrum are briefly discussed. This approach highlights the importance of the information spectrum in determining the limiting guessing exponent. All known prior results are then re-derived as example applications of our unifying approach.Comment: 16 pages, to appear in IEEE Transaction on Information Theor

Guessing under source uncertainty

This paper considers the problem of guessing the realization of a finite alphabet source when some side information is provided. The only knowledge the guesser has about the source and the correlated side information is that the joint source is one among a family. A notion of redundancy is first defined and a new divergence quantity that measures this redundancy is identified. This divergence quantity shares the Pythagorean property with the Kullback-Leibler divergence. Good guessing strategies that minimize the supremum redundancy (over the family) are then identified. The min-sup value measures the richness of the uncertainty set. The min-sup redundancies for two examples - the families of discrete memoryless sources and finite-state arbitrarily varying sources - are then determined.Comment: 27 pages, submitted to IEEE Transactions on Information Theory, March 2006, revised September 2006, contains minor modifications and restructuring based on reviewers' comment

Control Variates for Reversible MCMC Samplers

A general methodology is introduced for the construction and effective application of control variates to estimation problems involving data from reversible MCMC samplers. We propose the use of a specific class of functions as control variates, and we introduce a new, consistent estimator for the values of the coefficients of the optimal linear combination of these functions. The form and proposed construction of the control variates is derived from our solution of the Poisson equation associated with a specific MCMC scenario. The new estimator, which can be applied to the same MCMC sample, is derived from a novel, finite-dimensional, explicit representation for the optimal coefficients. The resulting variance-reduction methodology is primarily applicable when the simulated data are generated by a conjugate random-scan Gibbs sampler. MCMC examples of Bayesian inference problems demonstrate that the corresponding reduction in the estimation variance is significant, and that in some cases it can be quite dramatic. Extensions of this methodology in several directions are given, including certain families of Metropolis-Hastings samplers and hybrid Metropolis-within-Gibbs algorithms. Corresponding simulation examples are presented illustrating the utility of the proposed methods. All methodological and asymptotic arguments are rigorously justified under easily verifiable and essentially minimal conditions.Comment: 44 pages; 6 figures; 5 table

Decoding Protocols for Classical Communication on Quantum Channels

We study the problem of decoding classical information encoded on quantum states at the output of a quantum channel, with particular focus on increasing the communication rates towards the maximum allowed by Quantum Mechanics. After a brief introduction to the main theoretical formalism employed in the rest of the thesis, i.e., continuous-variable Quantum Information Theory and Quantum Communication Theory, we consider several decoding schemes. First, we treat the problem from an abstract perspective, presenting a method to decompose any quantum measurement into a sequence of easier nested measurements through a binary-tree search. Furthermore we show that this decomposition can be used to build a capacity-achieving decoding protocol for classical communication on quantum channels and to solve the optimal discrimination of some sets of quantum states. These results clarify the structure of optimal quantum measurements, showing that it can be recast in a more operational and experimentally-oriented fashion. Second, we consider a more practical approach and describe three receiver structures for coherent states of the electromagnetic field with applications to single-mode state discrimination and multi-mode decoding at the output of a quantum channel. We treat the problem bearing in mind the technological limitations faced nowadays in the field of optical communications: we evaluate the performance of general decoding schemes based on such technology and report increased performance of two schemes, the first one employing a non-Gaussian transformation and the second one employing a code tailored to be read out easily by the most common detectors. Eventually we characterize a large class of multi-mode adaptive receivers based on common technological resources, obtaining a no-go theorem for their capacity.Comment: PhD thesis. 171 pages, 16 figure

Quantum state discrimination with bosonic channels and Gaussian states

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 161-166).Discriminating between quantum states is an indispensable part of quantum information theory. This thesis investigates state discrimination of continuous quantum variables, focusing on bosonic communication channels and Gaussian states. The specific state discrimination problems studied are (a) quantum illumination and (b) optimal measurements for decoding bosonic channels. Quantum illumination is a technique for detection and imaging which uses entanglement between a probe and an ancilla to enhance sensitivity. I shall show how entanglement can help with the discrimination between two noisy and lossy bosonic channels, one in which a target reflects back a small part of the probe light, and the other in which all probe light is lost. This enhancement is obtained even though the channels are entanglement-breaking. The main result of this study is that, under optimum detection in the asymptotic limit of many detection trials, 6 dB of improvement in the error exponent can be achieved by using an entangled state as compared to a classical state. In the study of optimal measurements for decoding bosonic channels, I shall present an alternative measurement to the pretty-good measurement for attaining the classical capacity of the lossy bosonic channel given product coherent-state inputs. This new measurement has the feature that, at each step of the measurement, only projective measurements are needed. The measurement is a sequential one: the number of steps required is exponential in the code length, and the error rate of this measurement goes to zero in the limit of large code length. Although not physically practical in itself, this new measurement has a simple physical interpretation in terms of collective energy measurements, and may give rise to an implementation of an optimal measurement for lossy bosonic channels. The two problems studied in my thesis are examples of how state discrimination can be useful in solving problems by using quantum mechanical properties such as entanglement and entangling measurements.by Si Hui Tan.Ph.D