15,073 research outputs found
Contextual Query Using Bell Tests
Tests are essential in Information Retrieval and Data Mining in order to
evaluate the effectiveness of a query. An automatic measure tool intended to
exhibit the meaning of words in context has been developed and linked with
Quantum Theory, particularly entanglement. "Quantum like" experiments were
undertaken on semantic space based on the Hyperspace Analogue Language (HAL)
method. A quantum HAL model was implemented using state vectors issued from the
HAL matrix and query observables, testing a wide range of windows sizes. The
Bell parameter S, associating measures on two words in a document, was derived
showing peaks for specific window sizes. The peaks show maximum quantum
violation of the Bell inequalities and are document dependent. This new
correlation measure inspired by Quantum Theory could be promising for measuring
query relevance.Comment: 12 pages, 3 figure
Quantum Simulation Logic, Oracles, and the Quantum Advantage
Query complexity is a common tool for comparing quantum and classical
computation, and it has produced many examples of how quantum algorithms differ
from classical ones. Here we investigate in detail the role that oracles play
for the advantage of quantum algorithms. We do so by using a simulation
framework, Quantum Simulation Logic (QSL), to construct oracles and algorithms
that solve some problems with the same success probability and number of
queries as the quantum algorithms. The framework can be simulated using only
classical resources at a constant overhead as compared to the quantum resources
used in quantum computation. Our results clarify the assumptions made and the
conditions needed when using quantum oracles. Using the same assumptions on
oracles within the simulation framework we show that for some specific
algorithms, like the Deutsch-Jozsa and Simon's algorithms, there simply is no
advantage in terms of query complexity. This does not detract from the fact
that quantum query complexity provides examples of how a quantum computer can
be expected to behave, which in turn has proved useful for finding new quantum
algorithms outside of the oracle paradigm, where the most prominent example is
Shor's algorithm for integer factorization.Comment: 48 pages, 46 figure
Integrating memory context into personal information re-finding
Personal information archives are emerging as a new challenge for information retrieval (IR) techniques.
The userâs memory plays a greater role in retrieval from person archives than from other more traditional types of information collection (e.g. the Web), due to the large overlap of its content and individual human memory of the captured material. This paper presents a new analysis on IR of personal archives from a cognitive perspective. Some existing work on personal information management (PIM) has begun to employ human memory features into their IR systems. In our work we seek to go further, we assume that for IR in PIM system terms can be weighted not only by traditional IR methods, but also taking the userâs recall reliability into account. We aim to develop algorithms that
combine factors from both the system side and the user side to achieve more effective searching. In this paper, we discuss possible applications of human memory theories for this algorithm, and present results from a pilot study and a proposed model of data structure for the HDMs achieves
mARC: Memory by Association and Reinforcement of Contexts
This paper introduces the memory by Association and Reinforcement of Contexts
(mARC). mARC is a novel data modeling technology rooted in the second
quantization formulation of quantum mechanics. It is an all-purpose incremental
and unsupervised data storage and retrieval system which can be applied to all
types of signal or data, structured or unstructured, textual or not. mARC can
be applied to a wide range of information clas-sification and retrieval
problems like e-Discovery or contextual navigation. It can also for-mulated in
the artificial life framework a.k.a Conway "Game Of Life" Theory. In contrast
to Conway approach, the objects evolve in a massively multidimensional space.
In order to start evaluating the potential of mARC we have built a mARC-based
Internet search en-gine demonstrator with contextual functionality. We compare
the behavior of the mARC demonstrator with Google search both in terms of
performance and relevance. In the study we find that the mARC search engine
demonstrator outperforms Google search by an order of magnitude in response
time while providing more relevant results for some classes of queries
Implications of quantum automata for contextuality
We construct zero-error quantum finite automata (QFAs) for promise problems
which cannot be solved by bounded-error probabilistic finite automata (PFAs).
Here is a summary of our results:
- There is a promise problem solvable by an exact two-way QFA in exponential
expected time, but not by any bounded-error sublogarithmic space probabilistic
Turing machine (PTM).
- There is a promise problem solvable by an exact two-way QFA in quadratic
expected time, but not by any bounded-error -space PTMs in
polynomial expected time. The same problem can be solvable by a one-way Las
Vegas (or exact two-way) QFA with quantum head in linear (expected) time.
- There is a promise problem solvable by a Las Vegas realtime QFA, but not by
any bounded-error realtime PFA. The same problem can be solvable by an exact
two-way QFA in linear expected time but not by any exact two-way PFA.
- There is a family of promise problems such that each promise problem can be
solvable by a two-state exact realtime QFAs, but, there is no such bound on the
number of states of realtime bounded-error PFAs solving the members this
family.
Our results imply that there exist zero-error quantum computational devices
with a \emph{single qubit} of memory that cannot be simulated by any finite
memory classical computational model. This provides a computational perspective
on results regarding ontological theories of quantum mechanics \cite{Hardy04},
\cite{Montina08}. As a consequence we find that classical automata based
simulation models \cite{Kleinmann11}, \cite{Blasiak13} are not sufficiently
powerful to simulate quantum contextuality. We conclude by highlighting the
interplay between results from automata models and their application to
developing a general framework for quantum contextuality.Comment: 22 page
- âŠ