BITS Faculty Publications

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Author: search.filters.author.Bitragunta, Sainath

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    Residual analysis based neutron-gamma pulses segregation of liquid scintillator detector
    (IOP, 2025-01) Bitragunta, Sainath
    An innovative residual analysis based method is proposed for pulse shape discrimination and segregation of neutron and gamma pulses of liquid scintillator-based detector (BC501A). This study develops a simple and efficient algorithm for discrimination of neutrons and gammas from mixed environment and then segregate the neutron and gamma pulses into two label datasets. This method involves analyzing the residuals between the measured pulse and the reference gamma pulse in normalized scale. By examining these residuals, users can identify characteristics unique to each type of radiation. The pulse shape discrimination performance obtained for a 5 inches by 5 inches (length by diameter) liquid scintillator detector using this residual method is found to be 20% better compared to that obtained using traditional charge comparison method.
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    Gauss-ramanujan functions: constructions, properties, and applications in communications and signal processing
    (2025-05) Bitragunta, Sainath
    In this article, I construct a new set of functions based on Ramanujan sequences (RSEs), Gaussian pulse (GP), and its delayed Gaussian pulse (DGP). The motivation for this construction is based on the special properties of RSEs, GP, and DGP. First, I present a procedure for constructing Gauss-Ramanujan (GauRam) functions using selected RSEs. I develop an insightful analysis for deterministic and stochastic overlap between GP and DGP. Specifically, I present exact and closed form approximation expressions for delay-averaged GP and DGP overlap and then evaluate them numerically. Later, I derive and analyze the mathematical (spectral) properties of selected GauRam functions. I extend the analysis by analyzing the Hilbert transform of the first-order GauRam function and validating orthogonality and its usefulness in analytic signal representations. Furthermore, I present insightful applications of these functions in communications and signal processing. Specifically, I present the continuous-wave Gauss-Ramanujan modulation (GRM) scheme, Gauss-Ramanujan Shift Keying (GRSK) scheme, and Gauss-Ramanujan wavelets and their analysis and comparisons with benchmarking. The desirable properties of these novel modulation schemes and wavelets enable their use in next-generation hybrid and energy-efficient communication systems and signal processing.
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    Functional analysis of neutron-gamma pulses and synthetic pulse generation for liquid scintillator
    (IEEE, 2025-08) Bitragunta, Sainath
    An innovative method is proposed to generate a realistic functional neutron and gamma pulses model for a liquid scintillator-based detector. This approach analyzed neutron and gamma pulse shapes, electronic noise and fit the model parameters that include the intrinsic properties of the scintillator and standard deviation of the transit time of the photomultiplier tube. The synthetic data are generated using Monte-Carlo-based statistical methods from the modeled functions, energy distributions of neutrons, gammas, and electronic noise. This work emulates realistic pulses that can be used to calibrate and test scintillation detectors used in nuclear physics experiments. This synthetic data library provides realistic labeled neutron and gamma pulses for liquid scintillators and photomultiplier tubes, which may be used for improving radiation detection through supervised machine learning. This study provides a comprehensive framework for neutron-gamma discrimination, synthetic data generation, and data validation.
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    Semi-supervised machine learning technique for neutron-gamma discrimination and generalized approach for figure of merit
    (IOP, 2025-08) Bitragunta, Sainath
    The discrimination between neutron and gamma radiation pulses is crucial in mixed environment for neutron spectroscopy, particularly in fields such as nuclear science, nuclear safety, environmental monitoring, and radiation imaging. A quantitative measurement is essential to evaluate the discriminatory performance and a generalized yardstick is desirable for all the available methods. This study introduces a semi-supervised machine learning approach utilizing Multi-Layer Perceptron, Convolutional Neural Network, Long Short-Term Memory Network and Transformer encoder-based classifier to perform neutron-gamma pulse discrimination. The proposed model is applied to pulse signals acquired from a liquid scintillator BC501A coupled with a photomultiplier tube R4144, recognized for their high sensitivity and effectiveness in neutron-gamma discrimination tasks. The model's performance is rigorously evaluated against traditional analogue and digital charge comparison discrimination techniques. A generalized method is introduced in terms of figure of merit for equipollent discrimination performance comparison with existing analog and digital-based methods as well as various other machine learning based classification techniques.
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    PUF-AQKD: a hardware-assisted quantum key distribution protocol for man-in-the-middle attack mitigation pdf
    (IEEE, 2025-05) Bhatia, Ashutosh; Bitragunta, Sainath; Tiwari, Kamlesh
    The Quantum Key Distribution (QKD) protocol utilizes quantum mechanics principles for cryptographic key exchange, ensuring absolute secrecy. Current QKD techniques are susceptible to man-in-the-middle (MITM) attacks due to the absence of an inherent mechanism for identity verification within the quantum channel. For authentication, these systems rely on classical or post-quantum cryptography, which diminishes the perfect security advantage provided by QKD. We present a Physical Unclonable Function (PUF)-based authenticated QKD protocol (PUF-AQKD), which avoids the necessity for authenticated classical channels and is useful in mitigating MITM attacks. The fundamental concept of PUF-AQKD is to implement a phase shift in the basis used for polarizing the transmitted qubits. The phase shift is dictated by PUFs, which are anticipated to result in analogous (correlated) responses for devices manufactured under similar conditions but dissimilar responses in different conditions. An adversary lacking a correlated PUF response shared by Alice and Bob would inadvertently increase the Quantum Bit Error Rates (QBER) observed at Bob’s end. We present a mathematical model to assess the efficacy of the proposed PUF-AQKD method and perform simulations utilizing the NetSquid simulator. The mathematical analysis and simulation findings indicate that PUF-AQKD can efficiently identify eavesdroppers, even during incomplete measurements, without the necessity of an authorized classical channel.
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    Adaptive RIS design and optimization for cooperative ris-assisted wireless systems
    (IEEE, 2025-07) Bitragunta, Sainath; Bhatia, Ashutosh
    We propose an adaptive RIS-based cooperative transmission strategy that jointly selects one of two RIS paths and dynamically optimizes the number of active meta-atoms to maximize physical layer (PHY) secrecy capacity under a total average power constraint. Unlike existing approaches that fix the RIS size K or assume identical fading on all links, our framework uses long-term statistics to probabilistically choose between two RISs (upper or lower) with arbitrary first-hop fading, and leverages instantaneous channel state information (CSI) on the selected path to solve a convex K-sizing problem via a Lagrangian multiplier approach. We derive and present the solution for optimal K, and numerically evaluate the average PHY secrecy capacity and average PHY secrecy efficiency for the proposed optimal strategy. Numerical results show that the proposed optimal-K strategy achieves up to 35% higher average PHY secrecy capacity and 50% improvement in average PHY secrecy efficiency compared to a fixed-K benchmark strategy across moderate power thresholds. Furthermore, we present an insightful asymptotic analysis for average PHY secrecy capacity in an interesting scaling regime. Our findings demonstrate the practical benefits of adaptive RIS for cooperative PHY secure and energy-efficient beyond fifth generation (B5G) wireless systems
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    Quantum key distribution optimization: reducing communication overhead in post-processing steps
    (IEEE, 2025-03) Bhatia, Ashutosh; Bitragunta, Sainath; Tiwari, Kamlesh
    Quantum Key Distribution (QKD) is a ground-breaking method in modern cryptography that uses quantum mechanics to establish secure communication channels. Unlike classical cryptographic techniques, QKD provides unconditional security based on quantum principles, such as the no-cloning theorem and the uncertainty principle. However, existing QKD systems often suffer from high overhead in key post-processing, affecting efficiency and scalability, especially in resource-constrained environments such as IoT. This paper addresses these challenges by introducing two key optimizations to enhance the efficiency and security of QKD systems. First, we propose a method using Pseudorandom Number Generators (PRNGs) to determine key bit positions for verification by Alice and Bob, significantly reducing communication over-head. Second, we employ hash-based subsequence comparison to minimize data exchange and leverage the cryptographic strength of hash functions. Results demonstrate that these strategies effectively reduce key post-processing overhead and improve the efficiency of QKD systems in real-world conditions making QKD more practical and scalable for diverse application contexts.
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    Efficient routing for QKD network using novel quantum optimization approach
    (IEEE, 2025) Bitragunta, Sainath; Bhatia, Ashuthosh
    With exponential growth and associated milestones set in quantum information and quantum computing (QC) technologies, QC is becoming a threat to existing key encryption strategies that leverage asymmetric cryptographic algorithms like RSA (Rivest, Shamir, Adleman) encryption. Since these algorithms form the backbone of Internet communication, it becomes essential to utilize secure quantum methods for key generation and distribution. The quantum key distribution (QKD) networks have since been extensively researched and implemented with various communication protocols, primarily utilizing the Quantum Entanglement and Quantum Key Correction paradigms. Efficient routing is one of the significant problems in classical and hybrid networks. It is important to propose novel hybrid and efficient routing protocols based on modern optimization approaches to design secure, fidelitous, and efficient quantum information networks. We perform this optimization by generating a cost function to implement quantum optimization algorithms, namely the Quantum Approximate Optimization Algorithm (QAOA). We further draw a comparison with the state-of-the-art graph theory-based optimization techniques. The primary objective of this paper is to fabricate a robust quantum communication network and to subsequently analyze the effectiveness of quantum based techniques to carry out network routing and link optimization, generating scope for the utilization of quantum architecture to enhance security in Q KD networks.
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    Enhanced lightweight quantum key distribution protocol for improved efficiency and security
    (IEEE, 2025) Bhatia, Ashutosh; Bitragunta, Sainath; Tiwari, Kamlesh
    Quantum Key Distribution (QKD) provides secure communication by leveraging quantum mechanics, with the BB84 protocol being one of its most widely adopted implementations. However, the classical post-processing steps in BB84, such as sifting, error correction, and key verification, often result in significant communication overhead, limiting its efficiency and scalability. In this work, we propose three key optimizations for BB84: (1) PRNG-based predetermined key bit positioning, which eliminates redundant bit exchanges during sifting, (2) hash-based subsequence comparison, enabling lightweight and efficient key verification, and (3) adaptive basis reconciliation, which minimizes the communication costs associated with basis matching. The proposed optimizations achieve a 50% reduction in communication overhead for large key sizes compared to traditional QKD protocols, as demonstrated through rigorous performance analysis. While the focus of this work is on the BB84 protocol, these optimizations are also directly applicable to a broader class of Discrete-Variable QKD (DV-QKD) protocols, such as six-state, B92, and E91, which share a fundamentally similar post-processing structure. This generality highlights the modularity and adaptability of the proposed methods across diverse QKD implementations. The proposed optimizations enhance post-processing efficiency and scalability, enabling practical deployment in bandwidth-limited environments like IoT networks, secure financial systems, and defense communications, thereby supporting broader adoption of quantum communication systems.
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    Quantum computing-accelerated kalman filtering for satellite clusters: algorithms and comparative analysis
    (IEEE, 2025-01) Bitragunta, Sainath; Bhatia, Ashutosh; Tiwari, Kamlesh
    The increasing demand for high-precision real-time data processing in satellite clusters requires efficient algorithms to manage inherent uncertainties in space-based systems. We propose an innovative framework that integrates Quantum Neural Network (QNN) architecture into Kalman filtering processes, specifically tailored for Low Earth Orbit satellite clusters. Our quantum computing-based approach achieves a significant improvement in prediction accuracy and a reduction in mean absolute error compared to classical Kalman filtering techniques. These advances significantly improve computational efficiency and error handling, making the method highly scalable under varying noise levels. A comparative analysis demonstrates the superior performance of the Quantum Kalman Filter in processing speed, resource utilization, and prediction accuracy, all evaluated within the constraints of LEO satellite constellations. These findings highlight the potential of quantum computing to optimize data processing strategies for future missions, including deep space explorations.