Quantum Computing based Implementation of Full Adder

Sohel, Mohammed Arifuddin; Zia, Naailah; Ali, Mohd Akef; Zia, Nida

doi:10.1109/inocon50539.2020.9298394

Cited by 9 publications

(5 citation statements)

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“…The SDK proposed in this paper extends ideas published by Sohel et al [4] and Vlatko et al [5] by constructing all the remaining circuits (adder, subtractor, increment, decrement, latch etc). These quantum circuits are combined to form and emulate all CPU instructions including but not limited to LOAD (latch), Arithmetic (adder, etc), Branch (C-not controlled) and bitwise logic (Quantum based logic gates) needed to implement a full instruction set.…”

Section: Overviewmentioning

confidence: 79%

“…The SDK contains three main components the first being an Intel 8080/Z80 emulator with pseudo RAM 3 , register 4 visibility and distinct methods for each instruction group. The second part contains an additional Python class which overrides the Intel 8080/Z80 instruction methods with new versions (Figure 1).…”

Section: Overviewmentioning

confidence: 99%

“…The term Pseudo RAM is used to describe a 2D array of 64k * 8 boolean variables which is used as RAM for the emulation class 4. A register is a small amount of internal (to the CPU) RAM.…”

mentioning

confidence: 99%

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A Software Development Kit and Translation Layer for Executing Intel 8080 Assembler on a Quantum Computer (August 2022)

Fitzjohn

Winckles

Wilson

et al. 2022

IEEE Trans. Quantum Eng.

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One of the major obstacles to the adoption of quantum computing is the requirement to define quantum circuits at the quantum gate level. Many programmers are familiar with high-level or lowlevel programming languages but not quantum gates nor the low-level quantum logic required to derive useful results from quantum computers. The steep learning curve involved when progressing from quantum gates to complex simulations such as Shor's algorithm has proven too much for many developers. The purpose of this paper and the software presented within, addresses this challenge by providing a Software Development Kit (SDK), translation layer, emulator and a framework of techniques for executing Intel 8080/Z80 assembler on a quantum computer, i.e. all salient points of CPU execution, logic, arithmetic and bitwise manipulation will be executed on the quantum computer using quantum circuits. This provides a novel means of displaying the equivalency and interoperability of quantum and classical computers. Developers and researchers can use the SDK to write code in Intel 8080/Z80 assembler which is executed locally via traditional emulation and remotely on a quantum computer in parallel. The emulator features side-by-side code execution with visibility of the running quantum circuit and re-usable/overridable methods. This enables programmers to learn, reuse and contrast techniques for performing any traditional CPU based technique/instruction on a quantum computer; e.g. a programmer may know how to multiply and perform checks on a classical CPU but is not able to perform the same tasks in a quantum implementation, this SDK allows the programmer to pick and choose the methods they would like to use to fulfil their requirements. The SDK makes use of open-source software, specifically Python and Qiskit for the emulation, translation, API calls and execution of user supplied code or binaries.

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Section: Overviewmentioning

confidence: 79%

Section: Overviewmentioning

confidence: 99%

See 1 more Smart Citation

A Software Development Kit and Translation Layer for Executing Intel 8080 Assembler on a Quantum Computer (August 2022)

Fitzjohn

Winckles

Wilson

et al. 2022

IEEE Trans. Quantum Eng.

View full text Add to dashboard Cite

show abstract

“…The efficiency gain, representing the relative performance improvement of quantum algorithms over classical ones, approaches zero. This observation indicates that quantum computing does not confer a substantial advantage in terms of computational efficiency for the specific tasks encompassed by QML Algorithm 1 and QML Algorithm 2 [11].…”

Section: Figure 1 Comparison Of Quantum and Classical Algorithmmentioning

confidence: 98%

Quantum Machine Learning for Advanced Threat Detection in Cybersecurity

Alluhaibi

2024

IJSSE

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“…In contrary to classical computers which work with state 0 or 1 binary bits, the quantum computers work based on quantum bits which also known as qubits. The qubits can be simultaneously in state 0 and 1 with additional superposition and entanglement properties exhibited [11]. Qubit is the quantum state and the smallest particle unit in quantum information [12].…”

Section: Quantum Secure Direct Communication (Qsdc)mentioning

confidence: 99%

Protocol Efficiency Using Multiple Level Encoding in Quantum Secure Direct Communication Protocol

Mohamad Rodzi,

Azahari,

Harun

2023

IJSECS

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One of the objectives of information security is to maintain the confidentiality and integrity of the information by ensuring that information is transferred in a way that is secure from any listener or attacker. There was no comparison experiment conducted in earlier studies regarding different level encoding performance towards the multiphoton technique. In Quantum Secure Direct Communication (QSDC), when unpolarized light enters into the polarizer, the light value will be changed into a different value when it hit the Half Wave Plate (HWP) along the quantum communication channel. The multiphoton technique in the earlier study is particular to transmission time for data transfer encoding and extra time for polarizers to change polarization angles, both of which contribute to longer transmission times. With four different sizes of qubits, the three simulation experiments are carried out using Python coding with 2,4 and 8 levels of encoding. Experiment results demonstrate that the most efficient average photon transmission derived from 18 qubit size ranges from 98.71% to 98.73% depending on encoding level. With 18 qubit size, the four-level encoding result has the highest average efficiency, followed by the eight-level and two-level encodings, respectively. 4-level encoding exhibits the highest average photon efficiency between 2 and 8-level encoding.

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Quantum Computing based Implementation of Full Adder

Cited by 9 publications

References 0 publications

A Software Development Kit and Translation Layer for Executing Intel 8080 Assembler on a Quantum Computer (August 2022)

A Software Development Kit and Translation Layer for Executing Intel 8080 Assembler on a Quantum Computer (August 2022)

Quantum Machine Learning for Advanced Threat Detection in Cybersecurity

Protocol Efficiency Using Multiple Level Encoding in Quantum Secure Direct Communication Protocol

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