arXiv subjects

Ramon Jose C. Bagunu

Publications and source records attributed to Ramon Jose C. Bagunu.

4 recordsLinked to original sources

arXiv2026

Voxel-aware oxygen kinetics resolves radiation-induced DNA damage retention across LET-oxygen conditions

Objective. Hypoxic tumor subvolumes resist radiation through elevated oxygen enhancement ratios (OER), yet no computational OER model is simultaneously particle-specific, mechanistically grounded, and fast enough for voxel-scale treatment planning. We present the VOxel-Aware Oxygen Model (VOxA) to address all three requirements. Approach. An Oxygen Model (OM) encodes particle-specific LET-OER dependence through dual sigmoidal transitions constrained to increase monotonically with atomic number Z, combined with Michaelis-Menten oxygen kinetics. A Voxel-Aware (VA) extension resolves per-DSB local energy heterogeneity via a calibrated particle-specific sensitivity parameter. Calibrated on 233 OER observations from 29 sources across 10 particle types (LET = 0.2-654 keV/um); DSB coordinates from TOPAS-nBio simulations. Main results. The OM achieves $R^2 = 0.719$ and MAE = 0.300 retention OER units; theoretical OER maximum 3.32 (2.4% from measurement), bootstrap median 3.37 [3.18, 4.09]. The composite $K_{\rm fix} + K_{\rm repair} = 2.82$ mmHg is tightly constrained despite high collinearity (r = 0.935). On the Furusawa heavy-ion subset, VOxA achieves 28.4% lower survival OER MAE than the clinical standard (63.1% on helium, 24.0% on carbon) and reproduces He < C < Ne Z-ordering that universal models cannot capture. The VA extension passes 18 tests confirming sample-size-invariant within-nucleus coefficient of variation of the per-DSB retention probability. VOxA evaluates in under $10^{-3}$ ms per voxel, more than $10^6$ times faster than Monte Carlo chemistry. Significance. VOxA is the first particle-specific OER model to reproduce Z-ordering analytically at clinical planning speed, validated on the largest OER calibration dataset for this model class. Committed-break coordinates at whole-nuclear scale provide the input for inter-break topological analysis and hypoxic LET painting.

physics.med-ph↗

arXiv2026

Adversarial Reinforcement Learning for Adaptive Eavesdropping in BB84 Quantum Key Distribution

BB84 quantum key distribution derives its security from a physical guarantee that any eavesdropper disturbs the channel in a statistically detectable way. Prior work evaluates this by assuming Eve attacks at a fixed, analytically optimized rate. We examine what happens when Eve is modeled instead as a learning agent. Classical reinforcement learning is used, specifically tabular Q-Learning, SARSA, and Double Q-Learning, to adaptive BB84 eavesdropping. This formulates the attacker's decision as a Markov Decision Process where the agent observes Quantum Bit Error Rate (QBER) feedback and decides, qubit by qubit, whether to intercept or pass. Experiments span three channel noise levels ($μ_{ch}\in\{1\%,3\%,5\%\}$) and are validated across five independent random seeds (45 training runs per condition, 10,000 episodes each). Against the best non-adaptive analytical baseline, Q-Learning reduces detection from $99.4\%$ to $0.28\%\pm0.27\%$ at $μ_{ch}=1\%$ while extracting approximately 10.5 correct bits per episode. This is a 355-fold reduction that is statistically significant ($p=0.020$, Mann-Whitney $U$ test). We also report the spontaneous emergence of an end-game burst, where agents independently learn to surge their attack rate at the final block. This exploit vanishes under randomized checkpoint intervals while stealth performance remains statistically indistinguishable. These results motivate the inclusion of adaptive adversary baselines in quantum cryptographic security evaluations.

quant-ph↗

arXiv2026

Topological structure of radiation-induced DNA damage encodes coupled LET-oxygen signatures

We present the first nuclear-scale persistent homology and Random Forest classification analysis of radiation-induced DNA double-strand break (DSB) topology across the clinical particle therapy range. Using TOPAS-nBio and the Voxel-Aware Oxygen model, we generated 2,450 simulated nuclei across 49 conditions (seven particle configurations, 0.2--70.7~keV/\textmu{}m; seven oxygen levels, 0.005--21\%~O$_2$) and extracted a 107-feature matrix across seven modalities. DSB topology encodes particle identity, Spread-Out Bragg Peak (SOBP) position, and oxygen tension in a three-tier hierarchy, with fidelity at each tier governed by the physical mechanism controlling it. Particle identity and SOBP position are exactly decodable (balanced accuracy = 1.000). Oxygen-level classification degrades monotonically with LET from 0.517 (electrons) to 0.189 (carbon distal SOBP), with a charge-driven non-monotonicity at the helium-to-carbon transition confirming that atomic number, not LET alone, governs topological discriminability. The joint 49-class task achieves balanced accuracy 0.346, seventeen times above chance. Per-class recall peaks universally at 0.5\%~O$_2$ (0.788--0.976 across all configurations), which is consistent with the OER curve inflection. Topological Summaries (persistent entropy, landscape integrals) dominate oxygen encoding at all LET ($η^2_{O_2} =\,$0.300--0.622). A partial-out test reveals two mechanistically separable channels: a count-mediated scale signal ($η^2_{O_2}$ survival ratio 0.062) and a count-independent shape signal preserved or enhanced in five of seven configurations (balanced accuracy survival ratio 1.011). Persistent entropy and landscape integrals, as novel radiobiological observables, provide a computational basis for characterizing oxygen-dependent damage topology in hypoxic tumor treatment planning.

physics.med-ph↗

arXiv2024

Quantization of the Hamilton Equations of Motion

One of the fundamental problems in quantum mechanics is finding the correct quantum image of a classical observable that would correspond to experimental measurements. We investigate for the appropriate quantization rule that would yield a Hamiltonian that obeys the quantum analogue of Hamilton's equations of motion, which includes differentiation of operators with respect to another operator. To give meaning to this type of differentiation, Born and Jordan established two definitions called the differential quotients of first type and second type. In this paper we modify the definition for the differential quotient of first type and establish its consistency with the differential quotient of second type for different basis operators corresponding to different quantizations. Theorems and differentiation rules including differentiation of operators with negative powers and multiple differentiation were also investigated. We show that the Hamiltonian obtained from Weyl, simplest symmetric, and Born-Jordan quantization all satisfy the required algebra of the quantum equations of motion.

quant-ph↗