Quantum Machine Learning

• Author : Siddhartha Bhattacharyya,Indrajit Pan,Ashish Mani,Sourav De,Elizabeth Behrman,Susanta Chakraborti
• Publisher : Walter de Gruyter GmbH & Co KG
• Release : 08 June 2020

Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system. While many proposals of quantum machine learning algorithms are still purely

• Author : Santanu Ganguly
• Publisher : Apress
• Release : 09 July 2021

Know how to adapt quantum computing and machine learning algorithms. This book takes you on a journey into hands-on quantum machine learning (QML) through various options available in industry and research. The first three chapters offer insights into the combination of the science of quantum mechanics and the techniques of machine learning, where concepts of classical information technology meet the power of physics. Subsequent chapters follow a systematic deep dive into various quantum machine learning algorithms, quantum optimization, applications of

• Author : Peter Wittek
• Publisher : Academic Press
• Release : 10 September 2014

Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary

• Author : Jordi Riu I Vicente
• Publisher : Unknown
• Release : 17 May 2021

We use reinforcement learning techniques to optimize the Quantum Approximate Optimization Algorithm when applied to the MaxCut problem. We explore Q-learning based techniques both for continuous and discrete action environments with regular and irregular graphs.

• Author : Maria Schuld
• Publisher : Unknown
• Release : 17 May 2021

• Author : Maria Schuld,Francesco Petruccione
• Publisher : Springer
• Release : 30 August 2018

Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses

• Author : Felix Andreas Faber
• Publisher : Unknown
• Release : 17 May 2021

• Author : Kristof T. Schütt,Stefan Chmiela,O. Anatole von Lilienfeld,Alexandre Tkatchenko,Koji Tsuda,Klaus-Robert Müller
• Publisher : Springer Nature
• Release : 03 June 2020

Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations

• Author : Andreas Miroslaus Wichert
• Publisher : World Scientific
• Release : 08 July 2020

This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making — the core disciplines of artificial intelligence.Most of the chapters were rewritten and extensive new materials were updated. New topics include quantum machine learning, quantum-like Bayesian networks and mind in Everett many-worlds.

• Author : Anupam Prakash
• Publisher : Unknown
• Release : 17 May 2021

Most quantum algorithms offering speedups over classical algorithms are based on the three techniques of phase estimation, amplitude estimation and Hamiltonian simulation. In spite of the linear algebraic nature of the postulates of quantum mechanics, until recent work by Lloyd and coauthors cite{LMR13, LMR13a, LMR13b} no quantum algorithms achieving speedups for linear algebra or machine learning had been proposed. A quantum machine learning algorithm must address three issues: encoding of classical data into a succinct quantum representation,

• Author : Neeraj Kumar,Alka Agrawal,Brijesh Kumar Chaurasia,Raees Ahmad Khan
• Publisher : Information Science Reference
• Release : 18 December 2020

"This book is for security experts as well as for IoT developers to help them understand the concepts related to quantum cryptography and classical cryptography and providing a direction to security professionals and IoT solution developers toward using approaches of Quantum Cryptography as available computational power increases"--

• Author : Philips Coleman Ph D
• Publisher : Unknown
• Release : 05 March 2021

Quantum Cоmрutіng іѕ a new аnd еxсіtіng fіеld аt thе intersection оf mаthеmаtісѕ, computer ѕсіеnсе аnd physics. It соnсеrnѕ a utilization оf quаntum mесhаnісѕ tо іmрrоvе the еffісіеnсу of computation. Hеrе wе present a gеntlе introduction tо ѕоmе оf thе ideas in quаntum computing. The paper begins by motivating thе сеntrаl іdеаѕ of quantum mесhаnісѕ аnd quаntum соmр

• Author : Dr. Makhamisa Senekane
• Publisher : Packt Publishing Ltd
• Release : 29 January 2021

Quantum computers have the potential to efficiently solve problems that are otherwise unmanageable for classical computers. This book takes a hands-on approach to help you explore the foundation of quantum information processing as well as associated methodologies and implementations to enable you to be productive in no time.

• Author : Srinjoy Ganguly,Thomas Cambier
• Publisher : Packt Publishing Ltd
• Release : 30 April 2021

Silq is a new high-level programming language to program quantum computers easily. Silq is set to revolutionize quantum programming just as the C programming language did for classical computers. Quantum Computing with Silq will prepare you for the quantum revolution and enable you to start building software and application programs for ...

• Author : GEORGE. CHAPLINE
• Publisher : Unknown
• Release : 17 May 2021