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Can a quantum system be probabilistically simulated by a classical (probabilistic, I assume) universal computer? In other words, a computer which will give the same probabilities as the quantum system does. The answer is certainly, No!' This is called the hidden-variable theorem: It is impossible to represent the result of quantum mechanics with a classical universal device.
- Richard P. Feynman’s lecture titled Simulating Physics with Computers

Quantum Computing


Quantum computing, an amalgamation of quantum physics, computer science and information theory. It promises to achieve what looks impossible for conventional computers – solving problems that even the fastest computers today cannot. D-Wave quantum computers is faster than fastest computers today.

Why choose RCQE?


Quantum computing offers capabilities that are far ahead of those of classical computers. While the classical computing arena used electronic bits to represent ‘1’ and ‘0’ (ON/OFF), quantum computers operate with “qubits” that can represent ‘1’ and ‘0’ simultaneously.

With the qubits representing atoms, ions, photons/electrons and control devices huge volumes of numerical calculations can be processed, resulting in super efficiency and increased computing speed. This is a big paradigm shift in the world of computing!

As an RCQ Engineer, you are equipped to handle and solve issues that would be considered impossible on conventional computer systems. Being an RCQE enables to excel in solving encryption and optimization problems. Studying molecular and atomic interactions or designing new materials or drugs, are easier for a RCQ Engineer.

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This next great technological revolution has far-reaching implications for job creation, economic growth and national security. We look forward to building upon efforts to support the quantum-smart workforce of the future and engage with government, academic and private-sector leaders to advance QIS.
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Quantum computers are really good at solving those problems where you’ve got an exponential number of permutations to try out, says Stanford Clark, IBM CTO for UK and Ireland. He also adds that, The tipping point as to where classical computers give way to quantum computers is in the 50-60 qubit mark.
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Bringing Quantum Computer to Everyday Life – The Benefits


Quantum computing is sure to penetrate into our everyday interaction with machines in a big way. From simulation of quantum systems, designing superconductors operating at room temperature, attempting molecular modelling research, efficient machine learning, to cybersecurity, quantum computing has already made a foray into the latest technical advancements.
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D-Wave Computing


The D-Wave Systems’ quantum computers promise to overtake the fastest supercomputers in solving specific complex problems. Troubleshooting and problem solving is executed based on the counterintuitive behavior of matter at the atomic level and quantum resistors. These quantum computers can also tackle bioscience or cybersecurity problems which are not possible with conventional computers. Though D-Wave quantum computers are very expensive as of today, they are preferred by global giants like Google, NASA, Lockheed Martin, etc. because they provide interaction between their machines through a cloud service.
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Job Role Of The RCQE


Organizations need to solve challenging problems in fields such as optimization, simulation, and machine learning. As an RCQE, you will be equipped to take up multiple job roles and tasks including:

  • Collaborating with world-class team of quantum physicists, quantum chemists, computer scientists, HPC software developers, and operations researchers.
  • Ensure systems-level improvements
  • Recasting problems to harness the power of quantum computing
  • Efficiently translate fundamental physics into engineering specifications
  • Design quantum circuits for deploying them as quantum computers
  • Building and maintaining the database solution required for operating a quantum computer
  • Documenting the control software that will allow successful operation of our quantum computers
  • Improve the performance of the system that runs quantum programs
  • Developing novel hybrid quantum-classical algorithms for solving computationally challenging problems
  • Focuses on prototyping, developing, testing and validating new ideas using object-oriented languages such as C++ and python and following good practices in continuous delivery, documentation, and testing
  • Supporting the development of a quantum computing software infrastructure project which involves the interfaces to a diverse set of gate-model quantum emulators
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Future Of Quantum Computing – The Demand For RCQE


The quantum computing technique is appropriate to handle specific types of tasks in future, for example the prime factorization of large numbers, encryption techniques, crack codes that could harm communications and financial transactions. Further quantum computing research could give release to newer types of processors, navigation mechanisms, encryption tools, sensors and security systems. Information theory is another field where quantum computing is going to play a greater role in future.

Apart from China and the European Union investing billions of dollars in quantum computing, the President of United States of America, Donal Trump has recently signed up for accelerating quantum computing R&D as a legislation.

Traffic optimization, election modelling, marketing, advertising applications, autonomous driving, are just some of the innumerable sectors waiting for the pathbreaking quantum computing revolution to carry out calculations on a larger system of data and compute optimal real-time values.
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What Are The Skills Or Prerequisites To Become RCQE?


Quantum computing being a very technical as well as a highly complex and integrated field of study, the RCQE candidate should possess at least a Bachelor degree in any of the following disciplines:

  • Physics
  • Mathematics & Statistics
  • Computer science
  • Electrical and electronic engineering
  • Systems engineering
  • Software engineering

Knowledge and exposure to computational biology, quantum cryptography machine learning algorithms and programming languages would be very beneficial.
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Which are the industries waiting to hire the RCQEs?


Multinationals such as Microsoft, Google, IBM, Accenture, Airbus, Toshiba, Hitachi, and many more have heavily invested in quantum computing. Apart from them, several companies in the computing, technology, hardware, communications and metrology sectors are increasingly looking for skilled quantum engineers. Rocheston is the leader in the certification industry to help and train you to be the best QE!

Rocheston can help you in your amazing journey as an RCQE with access to its exhaustive course materials, interactive sessions and innovative training solutions. World over, companies are focussing on various business applications of quantum computing to bring about faster solutions leaving competitors far behind and that frontier is where Rocheston aims to prepare you for!

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RCQ Engineer Course Structure


  • A 5-day Training Program
  • Time: 9:30 AM – 6 PM
  • Provision of an active web Portal
  • Seminars conducted by qualified engineers
  • Best in-class environment
  • Exam can be taken on Rocheston
  • Cyberclass or Pearson VUE testing platform

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Rocheston Certified Quantum Computing Engineer Exam


• You can take the RCQE exam at Cyberclass®
• The training prepares you for the RCQE exam
• The exam consists of 50 multiple choice questions.
• The passing score is 70%
• You can attempt the exam multiple times until you pass the test

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Rocheston Certified Quantum Computing Engineer


This certificate will open many doors for you. Quantum Engineers are the most sought after professionals in the tech industry today.
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RCQE Course Outline

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View Course Outline Here
Module 1: Introduction to Quantum Computing

• What is Quantum Computing?
• Computability
• Programming Languages
• Quantum Bits

Module 2: Quantum Computing Basics

• Mystery of Probabilistic √I Gate
• Qbits and Qregisters
• Elementary Quantum Gates
• General Description of the Interferometer
• How to Prepare an Arbitrary Superposition

Module 3: Turing Machines

• Classical Turing Machine
• Nondeterministic and Probabilistic Computation
• Quantum Turing
• Modifications of the Base Model
• Generalized Quantum Turing Machine
• Classically Controlled Quantum Turing Machine
• Quantum Complexity
• Fantasy Quantum Computing

Module 4: Quantum Finite State Automata

• Finite Automata
• Deterministic Finite Automata
• Nondeterministic Finite Automata
• Probabilistic Automata
• Quantum Finite Automaton
• Measure-once Quantum Finite Automaton
• Measure-many Quantum Finite Automaton

Module 5: Q# (Q-sharp)

• The Type Model
• Expressions
• Statements
• File Structure

Module 6: A Brief Introduction To Information Theory

• Classical Information
• Information Content in a Signal
• Entropy and Shannon’s Information Theory
• Probability Basics

Module 7: Qubits and Quantum States

• The Qubit
• Vector Spaces
• Linear Combinations of Vectors
• Uniqueness of a Spanning Set
• Basis and Dimension
• Inner Products
• Orthonormality
• Gram-Schmidt Orthogonalization
• Bra-Ket Formalism
• The Cauchy-Schwartz and Triangle Inequalities

Module 8: Random Access Machines

• Classical RAM models
• Elements of RAM Model
• RAM-ALGOL
• Quantum RAM Model
• Quantum Pseudocode
• Elements of Quantum Pseudocode
• Quantum Conditions
• Measurement

Module 9: Computational Circuits

• Computational Circuits
• Boolean Circuits
• Reversible Circuits
• Universal Reversible Gates
• Quantum Circuits

Module 10: Matrices and Operators

• The Pauli Operators
• Outer Products
• The Closure Relation
• Representations of Operators Using Matrices
• Outer Products and Matrix Representations
• Matrix Representation of Operators in Two-Dimensional Spaces
• Definition: The Pauli Matrices
• Hermitian, Unitary, and Normal Operators
• Definition: Hermitian Operator
• Definition: Unitary Operator
• Definition: Normal Operator
• Eigenvalues and Eigenvectors
• The Characteristic Equation
• Spectral Decomposition
• The Trace of an Operator
• Important Properties of the Trace
• Functions of Operators
• Unitary Transformations
• Projection Operators
• Positive Operators
• Commutator Algebra
• The Heisenberg Uncertainty Principle
• Polar Decomposition and Singular Values
• The Postulates of Quantum Mechanics


Module 11: Tensor Products

• Representing Composite States in Quantum Mechanics
• Computing Inner Products
• Tensor Products of Column Vectors
• Operators and Tensor Products
• Tensor Products of Matrices

Module 12: The Density Operator

• The Density Operator for a Pure State
• Definition: Density Operator for a Pure State
• Definition: Using the Density Operator to Find the Expectation Value
• Time Evolution of the Density Operator
• Definition: Time Evolution of the Density Operator
• The Density Operator for a Mixed State
• Key Properties of a Density Operator
• Expectation Values
• Probability of Obtaining a Given Measurement Result
• Characterizing Mixed States
• Probability of Finding an Element of the Ensemble in a Given State
• Completely Mixed States
• The Partial Trace and the Reduced Density Operator
• The Density Operator and the Bloch Vector

Module 13: Quantum Programming Environment

• Architecture Components
• Quantum Intermediate Representation
• Quantum Assembly Language
• Quantum Physical Operations Language
• XML-based Representation of Quantum Circuits
• Basic Elements
• External Circuits

Module 14: Quantum Programming Languages

• Why Study Quantum Programming Languages
• Quantum Programming Basics
• Requirements for a Quantum Programming Language
• Basic Features of Existing Languages
• Imperative Languages
• Functional Languages


Module 15: Imperative Quantum Programming

• Quantum Computation Language (QCL)
• Basic Elements
• Quantum Memory Management
• Classical and Quantum Procedures and Functions
• Quantum Conditions
• LanQ
• Basic Elements
• Process Creation
• Communication
• Types

Module 16: Functional Quantum Programming

• Functional Modeling of Quantum Computation
• cQPL
• Classical Elements
• Quantum Elements
• Quantum Communication
• Qt Modeling Language (QML)
• Program Structure

Module 17: Quantum Measurement Theory

• Distinguishing Quantum States and Measurement
• Projective Measurements
• Measurements on Composite Systems
• Generalized Measurements
• Positive Operator-Valued Measures

Module 18: Entanglement

• Bell’s Theorem
• Bipartite Systems and the Bell Basis
• When Is a State Entangled?
• The Pauli Representation
• Entanglement Fidelity
• Using Bell States For Density Operator Representation
• Schmidt Decomposition

Module 19: Quantum Gates and Circuits

• Classical Logic Gates
• Single-Qubit Gates
• More Single-Qubit Gates
• Exponentiation
• The Z–Y Decomposition
• Basic Quantum Circuit Diagrams
• Controlled Gates
• Gate Decomposition

Module 20: Quantum Algorithms

• Hadamard Gates
• Matrix Representation of Serial and Parallel Operations
• Quantum Interference
• Quantum Parallelism and Function Evaluation
• Deutsch-Jozsa Algorithm
• Quantum Fourier Transform
• Phase Estimation
• Shor’s Algorithm
• Quantum Searching and Grover’s Algorithm
• Simon’s Algorithm
• Bernstein-Vazirani Algorithm


Module 21: Quantum Computing and Cryptography

• Quantum Cryptography
• A Brief Overview of RSA Encryption
• Basic Quantum Cryptography
• An Example Attack: The Controlled NOT Attack
• The B92 Protocol
• The E91 Protocol (Ekert)


Module 22: Quantum Noise and Error Correction

• Single-Qubit Errors
• Quantum Operations and Krauss Operators
• The Depolarization Channel
• The Bit Flip and Phase Flip Channels
• Amplitude Damping
• Phase Damping
• Quantum Error Correction
• Measurement Error Mitigation
• Calibrating Qubits with OpenPulse
• Randomized Benchmarking
• Measuring Quantum Volume



Module 23: Quantum Information Theory

• Tools of Quantum Information Theory
• The No-Cloning Theorem
• Trace Distance
• Entanglement of Formation and Concurrence
• Information Content and Entropy

Module 24: Adiabatic Quantum Computation

• Adiabatic Theorem
• Adiabatic Processes
• Adiabatic Quantum Computing


Module 25: Cluster State Quantum Computing

• Cluster States
• Cluster State Preparation
• Adjacency Matrices
• Stabilizer States
• Principles of Quantum Entanglement to Secure Communication (Unhackable networks)
• Aside: Entanglement Witness
• Cluster State Processing

Module 26: Microsoft Quantum Development Kit

• Q# language and compiler
• Q# library
• Local quantum machine simulator
• Quantum computer trace simulator
• Resource Estimator
• Visual Studio extension
• Visual Studio Code extension
• Qsharp for Python
• IQ#

Module 27: IBM’s Quantum Computing

• Remote Access via the REST API
• Qiskit
• IBM Q Experience
• Run a job
• Export API methods
• Debugging and Testing

Module 28: D-wave Quantum Computers

• Native Instances
• Mapping General Instance to Native Form
• The D-Wave Platform
• QSage Hybrid Optimizer

Module 29: Fujitsu “Quantum Inspired” Computer

• New Computing Perspective
• Digital Annealer
• Quantum-Inspired Architecture
• Logistics
• Radiation Therapy

Module 30: Qubit Signal Frequency Control in Quantum Advancement

• Precision Atom Qubits
• Quantum Computer Chip in Silicon
• CQC2T

Module 31: Jupyter Notebooks

• C#
• IQ#
• Jupyter
• Visual Studio
• Python
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