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Kridanto Surendro

Publications and source records attributed to Kridanto Surendro.

3 recordsLinked to original sources

Information-theoretic limits on undetectable parameter-estimation attacks in continuous-variable quantum key distribution

We formalize side-channel detection in Gaussian-modulated continuous-variable quantum key distribution (CV-QKD) as a certificate-forgery hypothesis test and identify its detectability with an information-theoretic rate. Relative to a set $\mathcal{M}$ of trusted, real-time-monitored observables, the forgery- detectability rate $g_{\mathcal M}$ of a benign-statistics certificate is the missed-detection Stein exponent. We prove a dichotomy: $g_{\mathcal M}$ is monotone and strictly positive in the leaked Holevo information when the shot- noise unit is trusted, and identically zero otherwise, recovering local- oscillator and calibration attacks as the degenerate case. Monotonicity yields a certificate reusability rate bounding the Holevo leakage compatible with an undetected certificate over $N_{\mathrm{PE}}$ estimation rounds, via the non- asymptotic bound $\varepsilon_{\mathrm{PE}}\le\exp(-N_{\mathrm{PE}}\psi(r))$ whose near-threshold expansion matches the Gaussian confidence-interval scaling of standard finite-size analyses. We then give a composable finite-size key- length statement under collective Gaussian attacks, whose worst-case Holevo term is the reusability rate and whose parameter-estimation failure probability is bounded by the Stein exponent at every block length. Both results are unconditional in the trusted-correlation model, where strict monotonicity of the Holevo leakage in the excess noise follows from a noise-injection argument; for general $\mathcal{M}$ they hold under an explicit no-spurious-local-minima condition on the divergence landscape, verifiable by low-dimensional inspection. Convexity of the rate further assumes a numerically supported concavity of the Holevo bound, the sole numerical ingredient; proof status is delimited throughout.

quant-ph

Dissipative Quantum Multiplicative Weights with Sampling Feedback: A Classically Hard Primitive Realized via Engineered Open-System Dynamics

We introduce \emph{Dissipative Quantum Multiplicative Weights with Sampling Feedback} (DQMW-Sample), an online-learning primitive in which engineered open quantum-system dynamics prepare a Gibbs state whose computational-basis measurement supplies the loss feedback. The central conceptual contribution is to lift the computational hardness of constant-temperature Gibbs sampling into a physically realizable online-learning primitive. By engineering a Davies-type dissipator whose per-round feedback cannot be efficiently simulated classically, we obtain a learning-theoretic separation in which DQMW-Sample achieves asymptotically sublinear regret while every efficient classical learner suffers constant average regret on a suitably constructed instance. We further prove that the spectral gap of the engineered dissipator contracts hardware noise, yielding sublinear noise-induced regret under a balanced dissipation schedule, and we strengthen the single-round hardness to the full adaptive interaction: an efficient classical simulator of the entire $T$-round feedback process would collapse the polynomial hierarchy. We state the required realizability assumption in explicit form and report an initial hardware characterization on the IBM Heron~r2 processor. These results position DQMW-Sample as a concrete route toward computational advantage in online learning that is grounded in complexity theory and compatible with near-term superconducting hardware.

quant-ph

Parameterized 4-Qubit EWL Quantum Game Circuits with Dirac-Solow-Swan Hamiltonian Integration for Quadruple Helix Disruptive Innovation Recommender Systems

We present a novel parameterized 4-qubit Eisert-Wilkens-Lewenstein (EWL) quantum game circuit for recommender systems in quadruple helix innovation ecosystems (academia, industry, government, and civil society). The local strategy operators $U_{i} = R_y(\theta_{i})$ for each helix actor are directly tuned by normalized dominance weights extracted from real participant funding data (\texit{ecContribution}) in the European Commission CORDIS Horizon Europe database (project COVend, ID 101045956). The circuit employs a multi-qubit EWL entangler followed by parameterized local rotations, inverse entangler, and full measurement, achieving only 22 gates and circuit depth 11 while scaling as $O(n)$ for $n$-round helix communications. Measurement probabilities after the quantum game serve as recommender scores for disruptive versus sustaining innovation trends. These scores are subsequently mapped into the diagonal Dirac potential of a Dirac-Solow-Swan Hamiltonian, enabling time-evolution simulation of capital accumulation and bifurcation dynamics under disruptive innovation. Numerical experiments on real CORDIS quadruple-helix collaboration networks demonstrate the circuit's NISQ compatibility and its ability to forecast disruptive capital trajectories with high fidelity. The proposed framework bridges quantum game theory, parameterized quantum circuits, and relativistic economic growth models, offering a computationally efficient tool for innovation policy and strategic decision-making in complex socio-economic ecosystems. Complexity analysis and reproducibility are provided through open Qiskit implementations.

quant-ph