DSpace Collection:
http://hdl.handle.net/10722/42586
2019-05-23T07:10:20ZAgents, subsystems, and the Conservation of Information
http://hdl.handle.net/10722/269779
Title: Agents, subsystems, and the Conservation of Information
Authors: Chiribella, G
Abstract: Dividing the world into subsystems is an important component of the scientific method. The choice of subsystems, however, is not defined a priori. Typically, it is dictated by our experimental capabilities, and, in general, different agents may have different capabilities. Here we propose a construction that associates every agent with a subsystem, equipped with its set of states and its set of transformations. In quantum theory, this construction accommodates the traditional notion of subsystems as factors of a tensor product, as well as the notion of classical subsystems of quantum systems. We then restrict our attention to systems where all physical transformations act invertibly. For such systems, the future states are a faithful encoding of the past states, in agreement with a requirement known as the Conservation of Information. For systems satisfying the Conservation of Information, we propose a dynamical definition of pure states, and show that all the states of all subsystems admit a canonical purification. This result extends the purification principle to a broader setting, in which coherent superpositions can be interpreted as purifications of incoherent mixtures. As an example, we illustrate the general construction for subsystems associated with group representations.2018-01-01T00:00:00ZQuantum speedup in testing causal hypotheses
http://hdl.handle.net/10722/269778
Title: Quantum speedup in testing causal hypotheses
Authors: Chiribella, G
Abstract: An important ingredient of the scientific method is the ability to test alternative hypotheses on the causal relations relating a given set of variables. In the classical world, this task can be achieved with a variety of statistical, information-theoretic, and computational techniques. In this talk I will address the extension from the classical scenario to the quantum scenario, and, more generally, to general probabilistic theories. After introducing the basic hypothesis testing framework, I will focus on a concrete example, where the task is to identify the causal intermediary of a given variable, under the promise that the causal intermediary belongs to a given set of candidate variables. In this problem, I will show that quantum physics offers an exponential advantage over the best classical strategies, with a doubling of the exponential decay of the error probability. The source of the advantage can be found in the combination of two quantum features: the complementarity between the information on the causal structure and other properties of the cause effect relation, and the ability to perform multiple tests in a quantum superposition. An interesting possibility is that one of the 'hidden principles' of quantum theory could be on our ability to test alternative causal hypotheses.2018-01-01T00:00:00ZData compression for quantum population coding
http://hdl.handle.net/10722/269777
Title: Data compression for quantum population coding
Authors: Chiribella, G
Abstract: Quantum states provide information about multiple,mutually complementary observables. Such information is not accessible from asingle system, but becomes accessible when a population of many identicallyprepared systems is available. In this context, an important question is howmuch information is contained into n copies of the same state. A rigorous wayto quantify such information is through the task of quantum data compression,where the goal is to store the quantum state into the smallest number ofquantum bits. The problem of compressing identically prepared systems isrelevant in several areas, including the design of quantum sensors thatcollect data and transfer them to a central location, and the design ofquantum learning machines that store patterns in their internal memory. Inthis talk I will characterize the minimum amount of memory needed tofaithfully store sequences of identically prepared quantum states, showinghow the size of the memory grows with the number of particles in thesequence. In addition, I will discuss how much quantum memory can be tradedwith classical memory. Finally, I will conclude by showing an application ofquantum compression to high precision measurements of time and frequency.
Description: Session VI: The Quantum Computing Promises I2018-01-01T00:00:00ZOptimal quantum compression for identically prepared systems
http://hdl.handle.net/10722/269776
Title: Optimal quantum compression for identically prepared systems; Optimal quantum compression for large statistical ensembles
Authors: Chiribella, G
Abstract: Quantum measurements extract probabilistic data, typically collected from sequences of identically prepared systems. When one such sequence is available, the experimenter can test different complementary observables But how much memory is required to faithfully store all this information in a quantum memory? The question is relevant in many areas, including the design of quantum sensors that collect statistical data and transfer it to a central location, where the data is processed. In this talk I will characterize the minimum amount of memory needed to faithfully store identical sequences of quantum states, showing how the size of the memory grows with the number of particles in the sequence and discussing how much quantum memory can be traded with classical memory. I will conclude by showing an application of quantum compression to high precision measurements of time and frequency.
Description: Keynote 9; Jointly Organized by Academy of Mathematics and Systems Science (AMSS) Chinese Academy of Sciences (CAS), Centre for Quantum Software and Information of University of Technology Sydney (UTS:QSI), and Algorithm & Complexity Group at Institute of Computing Technology (ICT), CAS2017-01-01T00:00:00Z