Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

International Conference on Machine Learning and Cybernetics

Simulating quantum computing: Quantum eXpress

Kareem S. Aggour, Renee Guhde, M.K. Sommins, M.J. Simon

Published May 13, 2004• 5 citations
Publisher

Abstract

Quantum computing (QC) research has gained a lot of momentum recently due to several theoretical analyses that indicate that QC is significantly more efficient at solving certain classes of problems than classical computing. While experimental validation will ultimately be required, the primitive nature of current QC hardware leaves practical testing limited to trivial examples. Thus, a robust simulator is needed to study complex QC issues. Most QC simulators model ideal operations, and thus cannot predict the actual time required to execute an algorithm or quantify the effects of errors in the calculation. We have developed a novel QC simulator that models physical hardware implementations. This simulator not only allows the accurate simulation of quantum algorithms on various hardware implementations, but also takes an important step towards providing a framework to determine their true performance and vulnerability to errors.

DOI
10.1109/wsc.2003.1261513

Related papers

Simulation and verification II: simulating quantum computing: quantum express

Kareem S. Aggour, Renee Guhde, Melvin K. Simmons +1 more

Quantum Computing (QC) research has gained a lot of momentum recently due to several theoretical analyses that indicate that QC is significantly more efficient at solving certain classes of problems than classical computing. While experimental validation will ultimately be required, the primitive nature of current QC hardware leaves practical testing limited to trivial examples. Thus, a robust simulator is needed to study complex QC issues. Most QC simulators model ideal operations, and thus cannot predict the actual time required to execute an algorithm or quantify the effects of errors in the calculation. We have developed a novel QC simulator that models physical hardware implementations. This simulator not only allows the accurate simulation of quantum algorithms on various hardware implementations, but also takes an important step towards providing a framework to determine their true performance and vulnerability to errors.

Winter Simulation Conference•Dec 7, 2003•0 citations

Quantum Computing Simulation

Manju S Nair, Jobin Johnson, Kiran Babu +1 more

Quantum computing is one of the emerging technologies with its immense capability, allowing us to solve computationally challenging problems more efficiently. Gaining a real quantum computer for running and testing algorithms is very costly. In order for developers and researchers to build and test algorithms, they can use simulators that can model the behaviour of a real quantum computer inside a classical computer. Simulating a quantum system on a classical machine is complex and requires a lot of processing power. This paper introduces some basic algorithms and methodologies we used to simulate an ideal multi-qubit simulator in classical terms

International Journal of Advanced Research in Science Communication and Technology•Jul 30, 2023•0 citations

Efficient quantum computing simulation through dynamic matrix restructuring and distributed evaluation

Kareem S. Aggour, Robert M. Mattheyses, Joseph Shultz

Quantum computing has the potential to revolutionize the field of computing, but with hardware and algorithms unlike any in use today. Due to the primitive state of existing quantum hardware, simulation is one of the most effective methods for studying quantum computing issues. Our team previously developed a general-purpose simulator capable of modeling arbitrary quantum algorithms executing on any hardware device. The simulator performs over a thousand matrix multiplications per step as part of its operations. To improve the simulator performance, optimizations were designed to dynamically restructure the problem. The resulting calculations were then distributed across a cluster. These enhancements reduced both the order of the simulator operations and the memory overhead, achieving an overall performance improvement of 99.94% from the initial implementation of a key quantum algorithm, reducing the simulator run time for this algorithm from two days on a single processor to under two minutes on a cluster.

IEEE International Conference on Cluster Computing (CLUSTER)•Jan 1, 2007•2 citations

Research of Quantum Neural Networks and Development of a Single-qubit Model of Neuron

Sergey M. Gushanskiy, Viktor Potapov, Alexey Samoylov

Recently, there has been a rapid increase interest in quantum computers. Their work is based on the use of quantum-mechanical phenomena such as superposition and entanglement for computing to transform input data into outputs, which can actually provide effective performance 3-4 orders of magnitude higher than any modern computing devices. In the past few decades, there has been an acute problem of creating a quantum computer that uses quantum mechanical effects for computations. Currently, there are prototypes of devices of this class, but it is not yet possible to achieve an effective solution to the planned tasks with their help due to a number of difficulties in implementation. However, there is a mathematical apparatus that describes the behavior of quantum particles using a wave function. Hence, it becomes possible to simulate quantum computations on the classical architecture and check the reliability of algorithms belonging to the NP class, which are theoretically executed on a quantum computer in polynomial time and which cannot be solved on classical computers within an acceptable time frame. Effectively simulate the operation of a quantum system on devices with classical architecture is impossible, it remains to propose methods for acceleration of quantum computing on classical systems.

Panhellenic Conference on Informatics•Nov 26, 2021•1 citation

Implementation and Performance Analysis of the Deutsch–Jozsa Quantum Algorithm Using Qiskit

Dr CH Pavan Satish, M.Anvesh, K.Bhavana +2 more

The quantum computing is a giant leap forward in comparison with our common computer models as it allows us to solve some problems with a much smaller number of steps. In this paper, we will demonstrate the design, development, and testing of the DeutschJozsa quantum algorithm using Qiskit. The algorithm can determine whether a Boolean function is identical or evenly divides with a single special query where traditional algorithms may require as many as 2n -1 +1 checks in the worst-case. We simulated the algorithm on an ideal simulator (Qiskit Aer) and IBM Quantum real hardware. Three aspects that we examined were the measurement accuracy, the depth of the quantum circuit, and how the noise of the real world, including decoherence and gate errors as well as readout errors, would influence the outcome of the NISQ devices. The simulator has nearly excellent precision, whereas the actual hardware has some visible disparities due to noise. These findings verify a undeniable quantum efficiency in query complexity and the cost decreases to a constant cost of O(1) quantum versus an exponential cost of O(2n) using a classical computer. Altogether, this paper is an example of quantum parallelism and quantum interference in a practical sense and serves as a good reference point to the capabilities of the current quantum hardware.

International Journal of Engineering Research and Science & Technology•Mar 22, 2026•0 citations

A Survey of Quantum Computing Security Protocols: Frameworks and Vulnerabilities

Dr Rajendirakumar S

Abstract Quantum computing promises unprecedented computational power, posing fundamental threats and offering novel solutions to modern cryptography and cybersecurity. This survey paper reviews the rapidly evolving landscape of quantum-resistant and quantum-native security protocols. By analyzing foundational computational security models and the unique vulnerabilities introduced by quantum algorithms, this work proposes a structured evaluation framework for assessing the robustness of cryptographic systems. Ultimately, this survey highlights the critical transition from classical cryptographic infrastructures to quantum-secure paradigms, ensuring data confidentiality and integrity in the post-quantum era. Keywords: Quantum Computing, Security Protocol, Vulnerabilities 1.Introduction The emergence of quantum computing represents a paradigm shift in both computational physics and information technology. Quantum algorithms, particularly Shor's and Grover's algorithms, inherently challenge the mathematical foundations of classical public-key cryptography. As a result, securing communication channels against quantum-empowered adversaries has become an urgent priority for global infrastructure and national security. The motivation for this survey stems from the immediate need to bridge the gap between theoretical quantum mechanics and applied cybersecurity, ensuring that secure communications can withstand the computational leaps expected in the next decade. The core problem addressed in this paper is the comprehensive evaluation of security protocols under the threat model of a fully scalable quantum computer. The scope encompasses both post-quantum cryptographic (PQC) protocols and inherently quantum protocols, such as those relying on physical quantum states for key distribution. Existing classical approaches are insufficient for two main reasons. First, classical computational security models often rely on mathematical hardness assumptions (like integer factorization) that are rapidly undermined by theoretical quantum algorithms. Second, current software tools for designing secure classical protocols fail to account for quantum state phenomena, such as superposition and entanglement, rendering classical verification methods inadequate for quantum threat models. To address these structural challenges, this paper presents the following contributions: We provide a comprehensive taxonomy of vulnerabilities in both classical and quantum security protocols, mapping specific algorithmic advantages to protocol failure points. We propose a structured, multi-module framework for simulating, attacking, and verifying the security of hybrid quantum-classical cryptographic architectures. 2.Foundations of Classical Protocol Analysis The rigorous analysis of security protocols has traditionally relied on well-defined computational and symbolic models (Toorani, 2016). Researchers have extensively mapped out the taxonomy of attacks on authenticated key exchange (AKE) protocols and password-authenticated key exchange (PAKE) systems, establishing the mathematical groundwork for secure communication. The core idea of these foundational works is to establish provable security bounds that distinguish between information-theoretic and computational security. While this traditional paradigm offers strong mathematical guarantees against classical adversaries, its primary weakness is the failure to incorporate quantum attack vectors into the adversary's capability profile. Our work builds upon these classical models by explicitly injecting quantum algorithmic capabilities into standard protocol verification routines. 2.1.Quantum Algorithm Development and Simulation A significant body of literature focuses on the theoretical development and computational simulation of quantum algorithms capable of compromising or enhancing network security. Academic overviews have formalized algorithms like Grover's and Shor's, demonstrating their theoretical efficiency over classical counterparts in breaking cryptographic primitives. Furthermore, researchers have developed advanced design automation tools, such as decision diagrams, to simulate and verify complex quantum circuits. The strength of these simulation tools lies in their ability to model complex quantum states without requiring expensive physical hardware. However, a notable weakness is that they often abstract away the physical noise and hardware constraints that exist in real-world cryptographic deployments. This survey contextualizes these simulation techniques specifically within the framework of adversarial security testing, bridging theoretical algorithms with practical protocol defense. 3.Physical Implementations and Hardware Considerations Beyond algorithmic theory, the physical realization of quantum states directly impacts the practical security of any quantum protocol. Research into cavity quantum electrodynamics (QED) has demonstrated the complete mathematical construction of fundamental quantum gates, such as the controlled-controlled NOT gate, operating in the weak coupling regime (Fujii et al., 2005). Additionally, methods like Quantum Computed Moments (QCM) address the hardware constraints and noise typical of Near-Term Intermediate Scale Quantum (NISQ) devices, estimating ground state properties even with suboptimal trial states. The strength of this hardware-focused research is its realism regarding current technological limits; however, it often lacks a direct bridge to high-level network protocol verification. Compared to these purely physical studies, our survey integrates physical noise models into a generalized, software-driven protocol verification framework. 4.Approach To systematically evaluate quantum computing security protocols, we propose a structured Quantum Protocol Verification Framework (QPVF). The first module is the "Threat Modeling Engine," which defines the adversary's capabilities, ranging from classical data interception to full quantum memory manipulation. The second module is the "Quantum Circuit Synthesizer," which leverages decision diagram-based tools to translate high-level cryptographic operations into verifiable quantum circuits. The final module is the "Vulnerability Analyzer," which subjects the synthesized circuits to simulated quantum attacks, effectively distinguishing between idealized computational security and realistic hardware-constrained security. This modular pipeline allows security engineers to isolate specific vulnerabilities at both the abstract algorithmic layer and the simulated physical implementation layer. A key design choice in the QPVF is the utilization of decision diagrams for circuit simulation. This choice is predicated on the fact that decision diagrams efficiently handle the exponential state space of quantum systems during complex verification tasks (Wille et al., 2021). Furthermore, our framework explicitly incorporates noise models derived from current NISQ hardware limitations, ensuring that the security evaluation reflects realistic physical constraints rather than purely idealized environments (Vallury & Hollenberg, 2023). To evaluate this framework, we propose a hypothetical benchmarking plan using an artificially generated dataset of 10,000 hybrid quantum-classical cryptographic key exchanges. We will measure the success rate of simulated Grover-based brute-force attacks against varying key sizes and simulated environmental noise levels. This evaluation will compare the theoretical vulnerability threshold of a protocol against the practical threshold observed when quantum noise severely degrades the adversary's computational capabilities. The operational flow of the QPVF is designed to provide end-to-end security verification for next-generation networks. It bridges the critical gap between abstract protocol design and simulated hardware execution. The methodology can be summarized by the following numbered pipeline: Protocol Ingestion: The classical or quantum protocol is parsed into a standardized symbolic representation. Adversary Assignment: The user assigns a precise computational profile, selecting between traditional classical algorithms or advanced quantum capabilities. Circuit Generation: Protocol steps are mapped to equivalent quantum decision diagrams for scalable software simulation. Execution & Attack: Simulated quantum algorithms are executed against the mapped circuits to test for cryptographic resilience. Output Generation: The system outputs a vulnerability score and highlights specific failure points caused by either algorithmic weaknesses or simulated hardware noise. 5.Discussion The transition to quantum-secure protocols carries profound practical implications for global information infrastructure and enterprise deployment. Deploying these advanced protocols requires immense updates to existing software toolkits, as current digital systems are not fundamentally designed to handle the complexity of quantum states. Furthermore, organizations must consider the massive educational and workforce development efforts needed to train software engineers in quantum cryptography, a requirement already highlighted by international hackathons and educational initiatives. Integrating quantum-resistant protocols into complex domains like high-energy physics networks or global banking systems will require bridging the gap between theoretical quantum mechanics and applied computer engineering. Consequently, practical deployment must occur in hybrid phases, maintaining classical cryptographic wrappers while dedicated quantum infrastructure matures. Despite the robust theoretical design of proposed quantum security frameworks, several limitations and failure modes persist in practical applications. First, physical implementation attacks, such as side-channel attacks on the lasers and cavities used in physical quantum gates can bypass theoretical software security guarant

•Mar 15, 2025•0 citations
Quantum computing (QC) research has gained a lot of momentum recently due to several theoretical analyses that indicate that QC is significantly more efficient at solving certain classes of problems than classical computing. While experimental validation will ultimately be required, the primitive nature of current QC hardware leaves practical testing limited to trivial examples. Thus, a robust simulator is needed to study complex QC issues. Most QC simulators model ideal operations, and thus cannot predict the actual time required to execute an algorithm or quantify the effects of errors in the calculation. We have developed a novel QC simulator that models physical hardware implementations. This simulator not only allows the accurate simulation of quantum algorithms on various hardware implementations, but also takes an important step towards providing a framework to determine their true performance and vulnerability to errors.
Quantum Computing (QC) research has gained a lot of momentum recently due to several theoretical analyses that indicate that QC is significantly more efficient at solving certain classes of problems than classical computing. While experimental validation will ultimately be required, the primitive nature of current QC hardware leaves practical testing limited to trivial examples. Thus, a robust simulator is needed to study complex QC issues. Most QC simulators model ideal operations, and thus cannot predict the actual time required to execute an algorithm or quantify the effects of errors in the calculation. We have developed a novel QC simulator that models physical hardware implementations. This simulator not only allows the accurate simulation of quantum algorithms on various hardware implementations, but also takes an important step towards providing a framework to determine their true performance and vulnerability to errors.
Quantum computing is one of the emerging technologies with its immense capability, allowing us to solve computationally challenging problems more efficiently. Gaining a real quantum computer for running and testing algorithms is very costly. In order for developers and researchers to build and test algorithms, they can use simulators that can model the behaviour of a real quantum computer inside a classical computer. Simulating a quantum system on a classical machine is complex and requires a lot of processing power. This paper introduces some basic algorithms and methodologies we used to simulate an ideal multi-qubit simulator in classical terms
Quantum computing has the potential to revolutionize the field of computing, but with hardware and algorithms unlike any in use today. Due to the primitive state of existing quantum hardware, simulation is one of the most effective methods for studying quantum computing issues. Our team previously developed a general-purpose simulator capable of modeling arbitrary quantum algorithms executing on any hardware device. The simulator performs over a thousand matrix multiplications per step as part of its operations. To improve the simulator performance, optimizations were designed to dynamically restructure the problem. The resulting calculations were then distributed across a cluster. These enhancements reduced both the order of the simulator operations and the memory overhead, achieving an overall performance improvement of 99.94% from the initial implementation of a key quantum algorithm, reducing the simulator run time for this algorithm from two days on a single processor to under two minutes on a cluster.
Recently, there has been a rapid increase interest in quantum computers. Their work is based on the use of quantum-mechanical phenomena such as superposition and entanglement for computing to transform input data into outputs, which can actually provide effective performance 3-4 orders of magnitude higher than any modern computing devices. In the past few decades, there has been an acute problem of creating a quantum computer that uses quantum mechanical effects for computations. Currently, there are prototypes of devices of this class, but it is not yet possible to achieve an effective solution to the planned tasks with their help due to a number of difficulties in implementation. However, there is a mathematical apparatus that describes the behavior of quantum particles using a wave function. Hence, it becomes possible to simulate quantum computations on the classical architecture and check the reliability of algorithms belonging to the NP class, which are theoretically executed on a quantum computer in polynomial time and which cannot be solved on classical computers within an acceptable time frame. Effectively simulate the operation of a quantum system on devices with classical architecture is impossible, it remains to propose methods for acceleration of quantum computing on classical systems.
The quantum computing is a giant leap forward in comparison with our common computer models as it allows us to solve some problems with a much smaller number of steps. In this paper, we will demonstrate the design, development, and testing of the DeutschJozsa quantum algorithm using Qiskit. The algorithm can determine whether a Boolean function is identical or evenly divides with a single special query where traditional algorithms may require as many as 2n -1 +1 checks in the worst-case. We simulated the algorithm on an ideal simulator (Qiskit Aer) and IBM Quantum real hardware. Three aspects that we examined were the measurement accuracy, the depth of the quantum circuit, and how the noise of the real world, including decoherence and gate errors as well as readout errors, would influence the outcome of the NISQ devices. The simulator has nearly excellent precision, whereas the actual hardware has some visible disparities due to noise. These findings verify a undeniable quantum efficiency in query complexity and the cost decreases to a constant cost of O(1) quantum versus an exponential cost of O(2n) using a classical computer. Altogether, this paper is an example of quantum parallelism and quantum interference in a practical sense and serves as a good reference point to the capabilities of the current quantum hardware.
Abstract Quantum computing promises unprecedented computational power, posing fundamental threats and offering novel solutions to modern cryptography and cybersecurity. This survey paper reviews the rapidly evolving landscape of quantum-resistant and quantum-native security protocols. By analyzing foundational computational security models and the unique vulnerabilities introduced by quantum algorithms, this work proposes a structured evaluation framework for assessing the robustness of cryptographic systems. Ultimately, this survey highlights the critical transition from classical cryptographic infrastructures to quantum-secure paradigms, ensuring data confidentiality and integrity in the post-quantum era. Keywords: Quantum Computing, Security Protocol, Vulnerabilities 1.Introduction The emergence of quantum computing represents a paradigm shift in both computational physics and information technology. Quantum algorithms, particularly Shor's and Grover's algorithms, inherently challenge the mathematical foundations of classical public-key cryptography. As a result, securing communication channels against quantum-empowered adversaries has become an urgent priority for global infrastructure and national security. The motivation for this survey stems from the immediate need to bridge the gap between theoretical quantum mechanics and applied cybersecurity, ensuring that secure communications can withstand the computational leaps expected in the next decade. The core problem addressed in this paper is the comprehensive evaluation of security protocols under the threat model of a fully scalable quantum computer. The scope encompasses both post-quantum cryptographic (PQC) protocols and inherently quantum protocols, such as those relying on physical quantum states for key distribution. Existing classical approaches are insufficient for two main reasons. First, classical computational security models often rely on mathematical hardness assumptions (like integer factorization) that are rapidly undermined by theoretical quantum algorithms. Second, current software tools for designing secure classical protocols fail to account for quantum state phenomena, such as superposition and entanglement, rendering classical verification methods inadequate for quantum threat models. To address these structural challenges, this paper presents the following contributions: We provide a comprehensive taxonomy of vulnerabilities in both classical and quantum security protocols, mapping specific algorithmic advantages to protocol failure points. We propose a structured, multi-module framework for simulating, attacking, and verifying the security of hybrid quantum-classical cryptographic architectures. 2.Foundations of Classical Protocol Analysis The rigorous analysis of security protocols has traditionally relied on well-defined computational and symbolic models (Toorani, 2016). Researchers have extensively mapped out the taxonomy of attacks on authenticated key exchange (AKE) protocols and password-authenticated key exchange (PAKE) systems, establishing the mathematical groundwork for secure communication. The core idea of these foundational works is to establish provable security bounds that distinguish between information-theoretic and computational security. While this traditional paradigm offers strong mathematical guarantees against classical adversaries, its primary weakness is the failure to incorporate quantum attack vectors into the adversary's capability profile. Our work builds upon these classical models by explicitly injecting quantum algorithmic capabilities into standard protocol verification routines. 2.1.Quantum Algorithm Development and Simulation A significant body of literature focuses on the theoretical development and computational simulation of quantum algorithms capable of compromising or enhancing network security. Academic overviews have formalized algorithms like Grover's and Shor's, demonstrating their theoretical efficiency over classical counterparts in breaking cryptographic primitives. Furthermore, researchers have developed advanced design automation tools, such as decision diagrams, to simulate and verify complex quantum circuits. The strength of these simulation tools lies in their ability to model complex quantum states without requiring expensive physical hardware. However, a notable weakness is that they often abstract away the physical noise and hardware constraints that exist in real-world cryptographic deployments. This survey contextualizes these simulation techniques specifically within the framework of adversarial security testing, bridging theoretical algorithms with practical protocol defense. 3.Physical Implementations and Hardware Considerations Beyond algorithmic theory, the physical realization of quantum states directly impacts the practical security of any quantum protocol. Research into cavity quantum electrodynamics (QED) has demonstrated the complete mathematical construction of fundamental quantum gates, such as the controlled-controlled NOT gate, operating in the weak coupling regime (Fujii et al., 2005). Additionally, methods like Quantum Computed Moments (QCM) address the hardware constraints and noise typical of Near-Term Intermediate Scale Quantum (NISQ) devices, estimating ground state properties even with suboptimal trial states. The strength of this hardware-focused research is its realism regarding current technological limits; however, it often lacks a direct bridge to high-level network protocol verification. Compared to these purely physical studies, our survey integrates physical noise models into a generalized, software-driven protocol verification framework. 4.Approach To systematically evaluate quantum computing security protocols, we propose a structured Quantum Protocol Verification Framework (QPVF). The first module is the "Threat Modeling Engine," which defines the adversary's capabilities, ranging from classical data interception to full quantum memory manipulation. The second module is the "Quantum Circuit Synthesizer," which leverages decision diagram-based tools to translate high-level cryptographic operations into verifiable quantum circuits. The final module is the "Vulnerability Analyzer," which subjects the synthesized circuits to simulated quantum attacks, effectively distinguishing between idealized computational security and realistic hardware-constrained security. This modular pipeline allows security engineers to isolate specific vulnerabilities at both the abstract algorithmic layer and the simulated physical implementation layer. A key design choice in the QPVF is the utilization of decision diagrams for circuit simulation. This choice is predicated on the fact that decision diagrams efficiently handle the exponential state space of quantum systems during complex verification tasks (Wille et al., 2021). Furthermore, our framework explicitly incorporates noise models derived from current NISQ hardware limitations, ensuring that the security evaluation reflects realistic physical constraints rather than purely idealized environments (Vallury & Hollenberg, 2023). To evaluate this framework, we propose a hypothetical benchmarking plan using an artificially generated dataset of 10,000 hybrid quantum-classical cryptographic key exchanges. We will measure the success rate of simulated Grover-based brute-force attacks against varying key sizes and simulated environmental noise levels. This evaluation will compare the theoretical vulnerability threshold of a protocol against the practical threshold observed when quantum noise severely degrades the adversary's computational capabilities. The operational flow of the QPVF is designed to provide end-to-end security verification for next-generation networks. It bridges the critical gap between abstract protocol design and simulated hardware execution. The methodology can be summarized by the following numbered pipeline: Protocol Ingestion: The classical or quantum protocol is parsed into a standardized symbolic representation. Adversary Assignment: The user assigns a precise computational profile, selecting between traditional classical algorithms or advanced quantum capabilities. Circuit Generation: Protocol steps are mapped to equivalent quantum decision diagrams for scalable software simulation. Execution & Attack: Simulated quantum algorithms are executed against the mapped circuits to test for cryptographic resilience. Output Generation: The system outputs a vulnerability score and highlights specific failure points caused by either algorithmic weaknesses or simulated hardware noise. 5.Discussion The transition to quantum-secure protocols carries profound practical implications for global information infrastructure and enterprise deployment. Deploying these advanced protocols requires immense updates to existing software toolkits, as current digital systems are not fundamentally designed to handle the complexity of quantum states. Furthermore, organizations must consider the massive educational and workforce development efforts needed to train software engineers in quantum cryptography, a requirement already highlighted by international hackathons and educational initiatives. Integrating quantum-resistant protocols into complex domains like high-energy physics networks or global banking systems will require bridging the gap between theoretical quantum mechanics and applied computer engineering. Consequently, practical deployment must occur in hybrid phases, maintaining classical cryptographic wrappers while dedicated quantum infrastructure matures. Despite the robust theoretical design of proposed quantum security frameworks, several limitations and failure modes persist in practical applications. First, physical implementation attacks, such as side-channel attacks on the lasers and cavities used in physical quantum gates can bypass theoretical software security guarant