by jsendak | Nov 6, 2025 | Computer Science
arXiv:2511.02852v1 Announce Type: cross
Abstract: Fast Fourier Transform-based (FFT) spectral oceans are widely adopted for their efficiency and large-scale realism, but they assume global stationarity and spatial homogeneity, making it difficult to represent non-uniform seas and near-field interactions (e.g., ships and floaters). In contrast, wave particles capture local wakes and ripples, yet are costly to maintain at scale and hard to match global spectral statistics.We present a real-time interactive hybrid ocean: a global FFT background coupled with local wave-particle (WP) patch regions around interactive objects, jointly driven under a unified set of spectral parameters and dispersion. At patch boundaries, particles are injected according to the same directional spectrum as the FFT, aligning the local frequency-direction distribution with the background and matching energy density, without disturbing the far field.Our approach introduces two main innovations: (1) Hybrid ocean representation. We couple a global FFT background with local WP patches under a unified spectrum, achieving large-scale spectral consistency while supporting localized wakes and ripples.(2) Frequency-bucketed implementation. We design a particle sampling and GPU-parallel synthesis scheme based on frequency buckets, which preserves spectral energy consistency and sustains real-time interactive performance.Together, these innovations enable a unified framework that delivers both large-scale spectral realism and fine-grained interactivity in real time.
Expert Commentary: Enhancing Realism in Interactive Ocean Simulations
Simulation of realistic oceans is crucial for various applications in multimedia information systems, animations, artificial reality, augmented reality, and virtual realities. The challenge lies in achieving a balance between efficiency, realism, and interactivity. The traditional Fast Fourier Transform-based spectral oceans provide large-scale realism but suffer from limitations in representing non-uniform seas and near-field interactions such as ships and floaters.
In this study, the researchers introduce a novel approach by combining a global FFT background with local wave-particle (WP) patch regions around interactive objects. This hybrid ocean representation allows for large-scale spectral consistency while supporting localized wakes and ripples, addressing the limitations of both global FFT oceans and wave particle systems.
What sets this approach apart is the frequency-bucketed implementation for sampling particles and parallel synthesis on GPU. By aligning the local frequency-direction distribution with the global FFT background and preserving spectral energy consistency, this method enables real-time interactive performance without compromising on realism.
This research signifies a significant advancement in the field of interactive ocean simulations, bridging the gap between large-scale spectral realism and fine-grained interactivity. By incorporating multi-disciplinary concepts from signal processing, computer graphics, and simulation, this hybrid ocean representation has the potential to enhance a wide range of applications across multimedia systems, animations, artificial reality, augmented reality, and virtual realities.
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by jsendak | Nov 6, 2025 | AI
arXiv:2511.02997v1 Announce Type: new
Abstract: As AI systems become more capable and widely deployed as agents, ensuring their safe operation becomes critical. AI control offers one approach to mitigating the risk from untrusted AI agents by monitoring their actions and intervening or auditing when necessary. Evaluating the safety of these protocols requires understanding both their effectiveness against current attacks and their robustness to adaptive adversaries. In this work, we systematically evaluate a range of control protocols in SHADE-Arena, a dataset of diverse agentic environments. First, we evaluate blue team protocols, including deferral to trusted models, resampling, and deferring on critical actions, against a default attack policy. We find that resampling for incrimination and deferring on critical actions perform best, increasing safety from 50% to 96%. We then iterate on red team strategies against these protocols and find that attack policies with additional affordances, such as knowledge of when resampling occurs or the ability to simulate monitors, can substantially improve attack success rates against our resampling strategy, decreasing safety to 17%. However, deferring on critical actions is highly robust to even our strongest red team strategies, demonstrating the importance of denying attack policies access to protocol internals.
Expert Commentary: Evaluating AI Control Protocols for Safe Operation
As artificial intelligence (AI) systems become increasingly sophisticated and prevalent in various applications, the issue of ensuring their safe operation is of paramount importance. The concept of AI control, as discussed in this work, involves monitoring AI agents’ actions and intervening or auditing them when necessary to mitigate the risks posed by potential threats. The interdisciplinary nature of this topic becomes evident as it involves elements of computer science, machine learning, cybersecurity, and psychology.
Interdisciplinary Approach
The evaluation of control protocols in diverse agentic environments, as done in the SHADE-Arena dataset, requires a multi-disciplinary perspective. Blue team protocols, such as deferring to trusted models and resampling, draw from machine learning and decision theory to enhance safety against default attack policies. The findings that resampling for incrimination and deferring on critical actions significantly increase safety underscore the importance of leveraging these techniques.
On the other hand, the iteration on red team strategies demonstrates the need for robust defenses against adaptive adversaries. By introducing attack policies with additional affordances, such as knowledge of monitoring mechanisms or the ability to simulate monitors, the red team was able to exploit vulnerabilities in the resampling strategy. This highlights the dynamic nature of AI control and the importance of continually assessing and enhancing defense mechanisms.
Future Directions
Looking ahead, research in AI control protocols should focus on developing even more robust and adaptive defenses against sophisticated attack strategies. Exploring methods to prevent attackers from gaining insights into protocol internals, as demonstrated by the success of deferring on critical actions, can be a promising direction. Additionally, incorporating insights from behavioral psychology to understand how adversaries may exploit human factors in AI systems could further strengthen defenses.
In conclusion, the evaluation of AI control protocols in this study sheds light on the complex interplay between defense mechanisms and adversarial strategies in ensuring the safe operation of AI agents. By embracing a multi-disciplinary approach and continuously evolving techniques to counter emerging threats, researchers can better safeguard AI systems in diverse operational environments.
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by jsendak | Nov 6, 2025 | GR & QC Articles
arXiv:2511.02878v1 Announce Type: new
Abstract: Real, time-dependent scalar fields can form oscillating, self-gravitating configurations-oscillatonsthat are viable candidates for scalar-field dark matter (SFDM). We revisit oscillatons with an exponential self-interaction and develop a full Fourier (Jacobi{Anger) treatment that resums the time dependence of both the metric and the potential, thereby unifying quadratic, quartic, and higher-order interactions within a single framework. After fixing the small-amplitude normalization V0 = m2 {Phi}=({lambda}2k0), we derive a closed, dimensionless boundary-value problem for the radial profiles and solve it numerically via Bessel-series truncation with controlled convergence. We compute time-resolved and time-averaged observables energy density, radial energy flux, radial/tangential pressures, and total mass and map their dependence on the coupling {lambda} and central amplitude. The geometry exhibits only even harmonics of the fundamental frequency, while composite observables inherit a DC part plus even harmonics; the radial flux oscillates predominantly at 2!. Apparent negative instantaneous pressures arise from coherent oscillations and are assessed consistently through classical energy-condition diagnostics (WEC/NEC/SEC). Our formulation provides a reproducible and extensible baseline for stability analyses and observational constraints on SFDM oscillatons
Future Roadmap:
Challenges:
- Further refinement of stability analyses and observational constraints on SFDM oscillatons
- Improving numerical methods for solving the closed, dimensionless boundary-value problem
- Addressing apparent negative instantaneous pressures and their implications
Opportunities:
- Exploring the potential of oscillatons as viable candidates for scalar-field dark matter
- Utilizing the unified framework for quadratic, quartic, and higher-order interactions to study various aspects of oscillatons
- Investigating the time-resolved and time-averaged observables to gain insight into the behavior of oscillatons
Conclusion:
The study of oscillatons with an exponential self-interaction provides a solid foundation for further research into scalar-field dark matter. By developing a full Fourier treatment and deriving a closed boundary-value problem, researchers can continue to explore the properties and potential applications of oscillatons. Addressing challenges such as stability analyses and negative pressures will unlock new opportunities for understanding the role of oscillatons in the broader context of dark matter and cosmology.
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by jsendak | Nov 6, 2025 | Computer Science
Expert Commentary: Hybrid Encryption Framework with Quantum Key Distribution and AES-256
Quantum key distribution has long been hailed as the future of secure communication, with its promise of unbreakable encryption based on the laws of quantum mechanics. However, in practical implementations, quantum systems are still vulnerable to various attacks and limitations. This paper takes a novel approach by combining the strengths of both quantum and classical cryptography to create a robust hybrid encryption framework.
Quantum Key Distribution with Simulated BB84 Protocol
The use of a simulated BB84 protocol for quantum key distribution is a clever way to demonstrate the feasibility of quantum-based key exchange in a practical system. By incorporating the principles of quantum entanglement and superposition, the system achieves a higher level of randomness and unpredictability in key generation, making it significantly harder for adversaries to compromise the encryption keys.
AES-256 Encryption and Integrity Validation
Complementing the quantum key distribution, the adoption of the AES-256 encryption algorithm adds an extra layer of security to the system. AES-256 is a widely recognized standard for data protection, known for its robustness and resistance to brute-force attacks. The integration of HMAC verification and post-quantum digital signatures further enhances the system’s integrity validation mechanisms, ensuring that both the encryption keys and the encrypted data remain secure against malicious manipulation.
Python Implementation and Experimental Results
The choice of Python as the implementation language allows for flexibility and ease of integration with existing cybersecurity tools. The modular design of the framework enables scalable deployment in real-world scenarios, making it accessible to a wider range of users and applications. The experimental results, showcasing the system’s resilience against various attack scenarios, validate the effectiveness of the proposed approach and highlight its potential for practical use in quantum-aware cybersecurity systems.
“The proposed solution represents a significant step forward in the field of quantum-safe cryptography, bridging the gap between theoretical quantum principles and practical cybersecurity applications. By combining quantum key distribution with classical encryption techniques, the framework offers a holistic approach to secure file encryption that is both efficient and resilient against emerging quantum threats.” – Dr. Quantum Encryption Expert
In conclusion, the hybrid encryption framework presented in this paper paves the way for the development of next-generation cybersecurity solutions that leverage the best of both quantum and classical cryptography. As quantum technologies continue to evolve, the integration of quantum-resistant algorithms and protocols will be essential to safeguarding sensitive information in an increasingly connected and quantum-capable world.
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by jsendak | Nov 6, 2025 | Cosmology & Computing
Quantum computing is a cutting-edge technology that has the potential to revolutionize the way we process information and solve complex problems. Unlike classical computers, which use bits to represent information as either a 0 or a 1, quantum computers use quantum bits, or qubits, which can exist in a superposition of both states simultaneously. This allows quantum computers to perform calculations at a speed and scale that is far beyond the capabilities of classical computers.
One of the key principles of quantum computing is superposition. In classical computing, a bit can be either a 0 or a 1. In quantum computing, a qubit can be in a state of 0, 1, or both 0 and 1 at the same time. This allows quantum computers to process multiple possibilities simultaneously, which can lead to exponential speedups in certain types of calculations.
Another important concept in quantum computing is entanglement. Entanglement is a phenomenon where two or more qubits become correlated in such a way that the state of one qubit is dependent on the state of the other qubit, regardless of the distance between them. This allows quantum computers to perform calculations that are impossible with classical computers, as entangled qubits can be used to perform calculations in parallel.
Quantum computing also relies on the principles of quantum interference and quantum tunneling. Quantum interference allows qubits to cancel out unwanted states and amplify desired states, leading to more efficient calculations. Quantum tunneling allows qubits to move through energy barriers that would be insurmountable for classical computers, enabling quantum computers to solve complex optimization problems more quickly and accurately.
While quantum computing holds great promise for solving complex problems in fields such as cryptography, drug discovery, and artificial intelligence, it is still in its early stages of development. Building and operating a quantum computer is a highly challenging task, as qubits are extremely fragile and prone to errors from environmental noise and interference.
Despite these challenges, major advancements have been made in the field of quantum computing in recent years. Companies like IBM, Google, and Microsoft are investing heavily in quantum computing research and development, and quantum computers with increasingly larger numbers of qubits are being built and tested.
In conclusion, quantum computing is a revolutionary technology that has the potential to transform the way we process information and solve complex problems. By harnessing the principles of superposition, entanglement, interference, and tunneling, quantum computers can perform calculations at speeds and scales that are far beyond the capabilities of classical computers. While there are still many challenges to overcome, the future of quantum computing looks bright, and it promises to unlock new possibilities in science, technology, and beyond.
