LEADER 00000nam a2200457 i 4500
001 978-1-4842-6516-1
003 DE-He213
005 20210317170808.0
006 m o d
007 cr nn 008maaau
008 201220s2020 cau s 0 eng d
020 9781484265161|q(electronic bk.)
020 9781484265154|q(paper)
024 7 10.1007/978-1-4842-6516-1|2doi
040 GP|cGP|erda|dAS
041 0 eng
050 4 QA76.889
082 04 006.3843|223
100 1 Kommadi, Bhagvan,|eauthor
245 10 Quantum computing solutions :|bsolving real-world problems
using quantum computing and algorithms /|cby Bhagvan
Kommadi
264 1 Berkeley, CA :|bApress :|bImprint: Apress,|c2020
300 1 online resource (xvii, 300 pages) :|billustrations,
digital ;|c24 cm
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
347 text file|bPDF|2rda
505 0 Part 1: Introduction -- Chapter 1: Quantum Solutions
Overview -- Chapter 2: Mathematics Behind Quantum
Computing -- Part 2: Quantum Computing Basics -- Chapter 3
: Quantum SubSystems and Properties -- Chapter 4: Quantum
Information Processing Framework -- Chapter 5: Quantum
Simulators -- Chapter 6: Quantum Optimization Algorithms -
- Chapter 7: Quantum Algorithms -- Chapter 8: Quantum
Neural Network Algorithms -- Chapter 9: Quantum
Classification Algorithms -- Chapter 10: Quantum Data
Processing -- Chapter 11: Quantum AI Algorithms -- Chapter
12: Quantum Solutions -- Chapter 13: Evolving Quantum
Solutions -- Chapter 14: Next Steps
520 Know how to use quantum computing solutions involving
artificial intelligence (AI) algorithms and applications
across different disciplines. Quantum solutions involve
building quantum algorithms that improve computational
tasks within quantum computing, AI, data science, and
machine learning. As opposed to quantum computer
innovation, quantum solutions offer automation, cost
reduction, and other efficiencies to the problems they
tackle. Starting with the basics, this book covers
subsystems and properties as well as the information
processing network before covering quantum simulators.
Solutions such as the Traveling Salesman Problem, quantum
cryptography, scheduling, and cybersecurity are discussed
in step-by-step detail. The book presents code samples
based on real-life problems in a variety of industries,
such as risk assessment and fraud detection in banking. In
pharma, you will look at drug discovery and protein-
folding solutions. Supply chain optimization and
purchasing solutions are presented in the manufacturing
domain. In the area of utilities, energy distribution and
optimization problems and solutions are explained.
Advertising scheduling and revenue optimization solutions
are included from media and technology verticals. You will
: Understand the mathematics behind quantum computing Know
the solution benefits, such as automation, cost reduction,
and efficiencies Be familiar with the quantum subsystems
and properties, including states, protocols, operations,
and transformations Be aware of the quantum classification
algorithms: classifiers, and support and sparse support
vector machines Use AI algorithms, including probability,
walks, search, deep learning, and parallelism
650 0 Quantum computing
650 0 Quantum computers
650 14 Big Data
650 24 Python
650 24 Quantum Computing
710 2 SpringerLink (Online service)
773 0 |tSpringer Nature eBook
856 40 |uhttps://doi.org/10.1007/978-1-4842-6516-1|zeBook
(SpringerLink)