We investigate faithful simulation of distributed quantum measurements as an extension of Winter's measurement compression theorem. We characterize a set of communication and common randomness rates needed to provide faithful simulation of distributed measurements. To achieve this, we introduce binning and mutual packing lemma for distributed quantum measurements. These techniques can be viewed as the quantum counterpart of their classical analogues. Finally, using these results, we develop a distributed quantum-to-classical rate distortion theory and characterize a rate region analogous to Berger-Tung's in terms of single-letter quantum mutual information quantities.
We investigate faithful simulation of distributed quantum measurements as an extension of Winter's measurement compression theorem. We characterize a set of communication and common randomness rates needed to provide faithful simulation of distributed measurements. To achieve this, we introduce binning and mutual packing lemma for distributed quantum measurements. These techniques can be viewed as the quantum counterpart of their classical analogues. Finally, using these results, we develop a distributed quantum-to-classical rate distortion theory and characterize a rate region analogous to Berger-Tung's in terms of single-letter quantum mutual information quantities.
We consider the task of faithfully simulating a distributed quantum measurement, wherein we provide a protocol for the three parties, Alice, Bob and Charlie, to simulate a repeated action of a distributed quantum measurement using a pair of non-product approximating measurements by Alice and Bob, followed by a stochastic mapping at Charlie. The objective of the protocol is to utilize minimum resources, in terms of classical bits needed by Alice and Bob to communicate their measurement outcomes to Charlie, and the common randomness shared among the three parties, while faithfully simulating independent repeated instances of the original measurement. To achieve this, we develop a mutual covering lemma and a technique for random binning of distributed quantum measurements, and, in turn, characterize a set of sufficient communication and common randomness rates required for asymptotic simulatability in terms of single-letter quantum information quantities. In the special case, where the Charlie’s action is restricted to a deterministic mapping, we develop a one-shot performance characterization of the distributed faithful simulation problem. Furthermore, using these results we address a distributed quantum rate-distortion problem, where we characterize the achievable rate distortion region through a single-letter inner bound. Finally, via a technique of single-letterization of multi-letter quantum information quantities, we provide an outer bound for the rate-distortion region.
We consider the task of faithfully simulating a quantum measurement, acting on a joint bipartite quantum state, in a distributed manner. In this setup, the constituent sub-systems of the joint quantum state are measured by two agents, Alice and Bob. A third agent, Charlie, receives the measurement outcomes sent by Alice and Bob. Charlie uses local and pairwise shared randomness to compute a bivariate function of the measurement outcomes. The objective of three agents is to faithfully simulate the given distributed quantum measurement acting on the given quantum state while minimizing the communication and shared randomness rates. We demonstrate a new inner bound to the rate region using random structured POVMs based on asymptotically good algebraic codes, and characterize the performance limit using single-letter quantum mutual information quantities. This new bound subsumes the largest known inner bound and improves upon it strictly for identified examples. One of the challenges in analyzing these structured POVMs is that they exhibit only pairwise independence and induce only uniform single-letter distributions. We address these in the non-commutative quantum setting, and provide a two-party distributed faithful simulation and function computation protocol.
In this work, we consider the task of faithfully simulating a quantum measurement, acting on a joint bipartite quantum state, in a distributed manner. In the distributed setup, the constituent sub-systems of the joint quantum state are measured by two agents, Alice and Bob. A third agent, Charlie receives the measurement outcomes sent by Alice and Bob. Charlie uses local and pairwise shared randomness to compute a bivariate function of the measurement outcomes. The objective of three agents is to faithfully simulate the given distributed quantum measurement acting on the given quantum state while minimizing the communication and shared randomness rates. We demonstrate a new achievable information-theoretic rate-region that exploits the bivariate function using random structured POVMs based on asymptotically good algebraic codes. The algebraic structure of these codes is matched to that of the bivariate function that models the action of Charlie. The conventional approach for this class of problems has been to reconstruct individual measurement outcomes corresponding to Alice and Bob, at Charlie, and then compute the bivariate function, achieved using mutually independent approximating POVMs based on random unstructured codes. In the present approach, using algebraic structured POVMs, the computation is performed on the fly, thus obviating the need to reconstruct individual measurement outcomes at Charlie. Using this, we show that a strictly larger rate region can be achieved. One of the challenges in analyzing these structured POVMs is that they exhibit only pairwise independence and induce only uniform single-letter distributions. To address this, we use nesting of algebraic codes and develop a covering lemma applicable to pairwise-independent POVM ensembles. Combining these techniques, we provide a multi-party distributed faithful simulation and function computation protocol.
Quantum algorithms require quantum computers performing logical operations on a sufficiently large number of entangled qubits. Unfortunately, state-of-the-art quantum computers can only operate on tens of qubits. A solution to this scalability challenge is to employ the distributed paradigm, where a network of small-scale quantum computers are used in a distributed manner. It is the aim of my work to study the fundamental limits of distributed quantum problems and to further enhance their performance by exploiting the structure inherent to these problems employing asymptotically good Algebraic codes. This thesis consists of two parts. The first part studies the task of faithfully simulating a distributed quantum measurement, wherein we provide a protocol for the three parties, Alice, Bob and {Charlie}, to simulate a repeated action of a distributed quantum measurement using a pair of non-product approximating measurements by Alice and Bob, followed by a stochastic mapping at {Charlie}. The objective of the protocol is to utilize minimum resources, in terms of classical bits needed by Alice and Bob to communicate their measurement outcomes to {Charlie}, and the common randomness shared among the three parties, while faithfully simulating independent repeated instances of the original measurement. We characterize a set of sufficient communication and common randomness rates required for asymptotic simulatability in terms of single-letter quantum information quantities. We further improve the results obtained in the above by exploiting the structure present in the Charlie's stochastic bivariate mapping using random structured POVMs based on asymptotically good algebraic codes. The algebraic structure of these codes is matched to that of the bivariate function that models the action of Charlie. This leads to the computation being performed on the fly, thus obviating the need to reconstruct individual measurement outcomes at Charlie. We provide examples to illustrate the information-theoretic gains attained by endowing POVMs with algebraic structure. As an application of the distributed measurement compression problem, we also demonstrate a multi-party purity distillation protocol. Concluding this part, we consider the lossy quantum source coding problem where the objective is to compress a given quantum source below its von Neumann entropy. Inspired by the duality connections between the rate-distortion and channel coding problems in the classical setting, we propose a new formulation for the lossy quantum source coding problem. We require that the reconstruction of the compressed quantum source fulfill a global error constraint and employ the notion of a ``posterior reference map'' to measure the reconstruction error. Using these, we characterize the asymptotic performance limit of this problem in terms of single-letter coherent information of the given posterior reference map. In the second part of this thesis, we study the advantage algebraic structured codes can provide, to the class of the classical-quantum network problems. In particular, we investigate two problems. Firstly, we consider the problem of communicating a general bivariate function of two classical sources observed at the encoders of a classical-quantum multiple access channel. We propose and analyze a coding scheme based on algebraic structured coset codes that enables the decoder to recover the desired function without recovering the sources themselves. We derive a new set of sufficient conditions that are weaker than the current known for identified examples. In addition, we analyze the performance of these algebraic codes toward studying the capacity of a special class of 3-user classical-quantum interference channel.
We show that quantum-to-classical channels, i.e., quantum measurements, can be asymptotically simulated by an amount of classical communication equal to the quantum mutual information of the measurement, if sufficient shared randomness is available. This result generalizes Winter's measurement compression theorem for fixed independent and identically distributed inputs to arbitrary inputs, and more importantly, it identifies the quantum mutual information of a measurement as the information gained by performing it, independent of the input state on which it is performed. Our result is a generalization of the classical reverse Shannon theorem to quantum-to-classical channels. In this sense, it can be seen as a quantum reverse Shannon theorem for quantum-to-classical channels, but with the entanglement assistance and quantum communication replaced by shared randomness and classical communication, respectively. The proof is based on a novel one-shot state merging protocol for classically coherent states as well as the postselection technique for quantum channels, and it uses techniques developed for the quantum reverse Shannon theorem.
This paper is concerned with quantum data compression of asymptotically many independent and identically distributed copies of ensembles of mixed quantum states. The encoder has access to a side information system. The figure of merit is per-copy or local error criterion. Rate-distortion theory studies the trade-off between the compression rate and the per-copy error. The optimal trade-off can be characterized by the rate-distortion function, which is the best rate given a certain distortion. In this paper, we derive the rate-distortion function of mixed-state compression. The rate-distortion functions in the entanglement-assisted and unassisted scenarios are in terms of a single-letter mutual information quantity and the regularized entanglement of purification, respectively. For the general setting where the consumption of both communication and entanglement are considered, we present the full qubit-entanglement rate region. Our compression scheme covers both blind and visible compression models (and other models in between) depending on the structure of the side information system.