107 research outputs found
Publications of the Jet Propulsion Laboratory July 1965 through July 1966
Bibliography on Jet Propulsion Laboratory technical reports and memorandums, space programs summary, astronautics information, and literature searche
Quantum Private Information Retrieval from Coded Storage Systems
In the era of extensive data growth, robust and efficient mechanisms are
needed to store and manage vast amounts of digital information, such as Data
Storage Systems (DSSs). Concurrently, privacy concerns have arisen, leading to
the development of techniques like Private Information Retrieval (PIR) to
enable data access while preserving privacy. A PIR protocol allows users to
retrieve information from a database without revealing the specifics of their
query or the data they are accessing.
With the advent of quantum computing, researchers have explored the potential
of using quantum systems to enhance privacy in information retrieval. In a
Quantum Private Information Retrieval (QPIR) protocol, a user can retrieve
information from a database by downloading quantum systems from multiple
servers, while ensuring that the servers remain oblivious to the specific
information being accessed. This scenario offers a unique advantage by
leveraging the inherent properties of quantum systems to provide enhanced
privacy guarantees and improved communication rates compared to classical PIR
protocols.
In this thesis we consider the QPIR setting where the queries and the coded
storage systems are classical, while the responses from the servers are
quantum. This problem was treated by Song et al. for replicated storage and
different collusion patterns. This thesis aims to develop QPIR protocols for
coded storage by combining known classical PIR protocols with quantum
communication algorithms, achieving enhanced privacy and communication costs.
We consider different storage codes and robustness assumptions, and we prove
that the achieved communication cost is always lower than the classical
counterparts.Comment: This is the summary part of an article collection-based PhD thesi
Classical-to-Quantum Sequence Encoding in Genomics
DNA sequencing allows for the determination of the genetic code of an
organism, and therefore is an indispensable tool that has applications in
Medicine, Life Sciences, Evolutionary Biology, Food Sciences and Technology,
and Agriculture. In this paper, we present several novel methods of performing
classical-to-quantum data encoding inspired by various mathematical fields, and
we demonstrate these ideas within Bioinformatics. In particular, we introduce
algorithms that draw inspiration from diverse fields such as Electrical and
Electronic Engineering, Information Theory, Differential Geometry, and Neural
Network architectures. We provide a complete overview of the existing data
encoding schemes and show how to use them in Genomics. The algorithms provided
utilise lossless compression, wavelet-based encoding, and information entropy.
Moreover, we propose a contemporary method for testing encoded DNA sequences
using Quantum Boltzmann Machines. To evaluate the effectiveness of our
algorithms, we discuss a potential dataset that serves as a sandbox environment
for testing against real-world scenarios. Our research contributes to
developing classical-to-quantum data encoding methods in the science of
Bioinformatics by introducing innovative algorithms that utilise diverse fields
and advanced techniques. Our findings offer insights into the potential of
Quantum Computing in Bioinformatics and have implications for future research
in this area.Comment: 58 pages, 14 figure
Space Programs Summary No. 37-36
Research in systems, guidance and control, space sciences, engineering, telecommunications and propulsion for space exploration program
Statistical perspectives on dependencies between genomic markers
To study the genetic impact on a quantitative trait, molecular markers are used as predictor variables in a statistical model. This habilitation thesis elucidated challenges accompanied with such investigations. First, the usefulness of including different kinds of genetic effects, which can be additive or non-additive, was verified. Second, dependencies between markers caused by their proximity on the genome were studied in populations with family stratification. The resulting covariance matrix deserved special attention due to its multi-functionality in several fields of genomic evaluations
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