arXiv subjects

G. Raghavan

Publications and source records attributed to G. Raghavan.

7 recordsLinked to original sources

arXiv2026

Benchmarking Quantum Algorithmic Resilience for CVaR Portfolio Optimization: The Expressibility-Coherence Trade-off

Quantum combinatorial optimization offers theoretical advantages for complex financial modeling, but physical implementation on Noisy Intermediate Scale Quantum (NISQ) devices is severely constrained by hardware topology. This study presents a hardware benchmarking analysis between a Hardware Efficient Variational Quantum Neural Network (HE-VQNN) and the Warm Start Quantum Approximate Optimization Algorithm (WS-QAOA) for a hybrid Mean Variance and Conditional Value at Risk (CVaR) portfolio objective. By implementing a novel classical quantum hybrid proxy matrix to bypass the CVaR auxiliary qubit bottleneck, we map up to 16 assets from the NIFTY 50 index onto an IBM heavy hex processor. We systematically quantify algorithmic resilience to the "SWAP tax" incurred during routing. Empirical results reveal a critical operational trade-off: WS-QAOA provides exact theoretical mapping but suffers catastrophic hardware decoherence due to exponential nonlocal gate overhead. Conversely, HE-VQNN preserves hardware coherence but lacks the mathematical expressibility to capture dense tail risk asset correlations. This study exposes the limitations of dense financial optimization on current architectures forces an nonviable choice between algorithmic inexpressibility and hardware decoherence. This is indicative of a deeper limitation as to what can and cannot be done with NISQ computers lacking in all-to-all connectivity.

quant-ph↗

arXiv2026

Engineering a Phase-Noise-Based Quantum Random Number Generator for Real-Time Secure Applications: Design, Validation, and Scalability

Random Number Generators (RNGs) are crucial for applications ranging from cryptography to simulations. Depending on the source of randomness, RNGs are classified into Pseudo-Random Number Generators (PRNGs), True Random Number Generators (TRNGs), and Quantum Random Number Generators (QRNGs). This work presents the end-to-end development of a high-speed, high-efficiency, phase-noise-based QRNG system that taps into the quantum phase noise of a single-frequency laser, with randomness originating from spontaneous emission. Using a self-heterodyne measurement with a semiconductor laser (linewidth $\approx$ 5.23 $GHz$) operated near threshold and a $\sim$48 $cm$ fiber delay line, a raw data generation rate of 2.0 $Gbps$ is achieved. To ensure uniform randomness in the QRNG output, robust extraction techniques developed in-house, such as the Toeplitz Strong Extractor (TSE), are used. Randomness validation using the NIST and Diehard test suites confirms that all statistical tests pass at standard confidence levels. The developed system achieves a post-processed generation rate of 1.0 $Gbps$ in operation and attains a Technology Readiness Level (TRL) of 7, approaching TRL 8, making it suitable for real-time secure applications such as cryptographic key generation and stochastic modeling.

quant-ph↗

arXiv2025

FPGA-based Toeplitz Strong Extractor for Quantum Random Number Generators

Quantum Random Number Generators (QRNGs) serve as high-entropy sources for Quantum Key Distribution (QKD) systems. However, the raw data from these quantum sources require post-processing to achieve a nearly uniform distribution. This work presents a state-of-the-art implementation of the Toeplitz Strong Extractor on an FPGA, achieving a benchmark extraction speed of 26.57 Gbps. A detailed implementation flow of the post-processing on the FPGA is provided, along with the execution speeds obtained for different randomness extraction ratios. Raw data from an in-house phase noise-based QRNG is processed on the FPGA using this implementation, and the output is validated using the NIST STS 2.1.2 statistical randomness test suite.

quant-ph↗

arXiv2017

Generalized reduction formula for Discrete Wigner functions of multiqubit systems

Density matrices and Discrete Wigner Functions are equally valid representations of multiqubit quantum states. For density matrices, the partial trace operation is used to obtain the quantum state of subsystems, but an analogous prescription is not available for discrete Wigner Functions. Further, the discrete Wigner function corresponding to a density matrix is not unique but depends on the choice of the quantum net used for its reconstruction. In the present work, we derive a reduction formula for discrete Wigner functions of a general multiqubit state which works for arbitrary quantum nets. These results would be useful for the analysis and classification of entangled states and the study of decoherence purely in a discrete phase space setting and also in applications to quantum computing

quant-ph↗

arXiv2016

Stokes vector and its relationship to Discrete Wigner Functions of multiphoton states

Stokes vectors and Discrete Wigner functions (DWF) provide two alternate ways of representing the polarization state of multiphoton systems. The Stokes vector associated with a n-photon polarization state is unique, and its Minkowski squared norm provides a direct way of quantifying entanglement through n-concurrence. However, the quantification of entanglement from DWF is not straight forward. The DWF associated with a given quantum state is not unique but depends on the way in which basis vectors are assigned to various lines in the phase space. For a Hilbert space of dimension N, there exists N N+1 such possible assignments. While a given DWF corresponds to a unique Stokes vector, the converse is not true. In the present work, we show that, for each particular assignment called a quantum net, there exist a unique Hadamard matrix which relates the Stokes vector to the corresponding DWF. This method provides an elegant and direct method of constructing the DWFs from the Stokes vector for every possible choice of the quantum net. Using these results, we derive the relationship between the Stokes vector of a spin-flipped state and the DWF. Finally, we also present a method to express the Minkowskian squared norm of the Stokes vector directly in terms of the DWF.

quant-ph↗

arXiv2016

Spin flip of multiqubit states in discrete phase space

Time reversal and spin flip are discrete symmetry operations of substantial import to quantum information and quantum computation. Spin flip arises in the context of separability, quantification of entanglement and the construction of Universal NOT gates. The present work investigates the relationship between the quantum state of a multiqubit system represented by the Discrete Wigner Function (DWFs) and its spin-flipped counterpart. The two are shown to be related through a Hadamard matrix that is independent of the choice of the quantum net used for the tomographic reconstruction of the DWF. These results would be of interest to cases involving the direct tomographic reconstruction of the DWF from experimental data and in the analysis of entanglement related properties purely in terms of the Discrete Wigner function.

quant-ph↗

arXiv2010

Generalization of the detailed fluctuation theorem for Non-Hamiltonian Dynamics

Detailed fluctuation theorem, a microscopic version of the steady state fluctuation theorem, has been proposed by Jarzynski and demonstrated in the case of Hamiltonian systems weakly coupled with reservoirs. We show that an identical theorem for phase space compressibility rate can be derived for systems evolving under non-Hamiltonian extended system dynamics, without certain limiting assumptions made in the original work. Our derivation is based on the non-Hamiltonian phase space formulation of statistical mechanics and does not rely on any assumptions of thermodynamic nature. This version of the detailed fluctuation theorem is shown to be generic enough to be applicable to several thermostatting schemes. It is shown that in equilibrium, this detailed fluctuation theorem boils down to the detailed balance equation and it is further shown to reproduce the Jarzynski's work theorem for driven systems.

cond-mat.stat-mech↗