Blog
Randomized Proper Orthogonal Decomposition for data-driven reduced order modeling of a two-layer quasi-geostrophic ocean model
The two-layer quasi-geostrophic equations (2QGE) serve as a simplified model for simulating wind-driven, stratified ocean flows. However, their numerical simulation remains computationally expensive due to the need for high-resolution meshes to capture a wide range of turbulent scales. This becomes especially problematic...
Efficiently learning fermionic unitaries with few non-Gaussian gates
Fermionic Gaussian unitaries are known to be efficiently learnable and simulatable. In this paper, we present a learning algorithm that learns an $n$-mode circuit containing $t$ parity-preserving non-Gaussian gates. While circuits with $t = \textrm{poly}(n)$ are unlikely to be efficiently learnable, for...
Dual Laser Self-Injection Locking to a Micro Fabry-Perot for Low Phase Noise Millimeter-wave Generation
Low-noise and accessible millimeter-wave sources are critical for emergent telecommunications, radar and sensing applications. Current limitations to realizing low-noise, deployable millimeter-wave systems include size, weight, and power (SWaP) requirements, along with complex operating principles. In this paper we provide a compact photonic...
LongPerceptualThoughts: Distilling System-2 Reasoning for System-1 Perception
Recent reasoning models through test-time scaling have demonstrated that long chain-of-thoughts can unlock substantial performance boosts in hard reasoning tasks such as math and code. However, the benefit of such long thoughts for system-2 reasoning is relatively less explored in other domains...
Logos-Zoe: A contact binary triple system in the trans-neptunian belt
The trans-neptunian object (58534) 1997 CQ$_{29}$ (a.k.a. Logos) is a resolved wide binary in the dynamically Cold Classical population. With Hubble Space Telescope resolved observations where the primary Logos is well separated from its secondary Zoe it can be established that Logos...
Convergence-rate and error analysis of sectional-volume average method for the collisional breakage equation with multi-dimensional modelling
Recent literature reports two sectional techniques, the finite volume method [Das et al., 2020, Siam J. Sci. Comput., 42(6): B1570-B1598] and the fixed pivot technique [Kushwah et al., 2023, Commun. Nonlinear Sci. Numer. Simul., 121(37): 107244] to solve one-dimensional collision-induced nonlinear particle...
FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching
Federated learning (FL) is a machine learning paradigm that facilitates massively distributed model training with end-user data on edge devices directed by a central server. However, the large number of heterogeneous clients in FL deployments leads to a communication bottleneck between the...
FLARE: Feature-based Lightweight Aggregation for Robust Evaluation of IoT Intrusion Detection
The proliferation of Internet of Things (IoT) devices has expanded the attack surface, necessitating efficient intrusion detection systems (IDSs) for network protection. This paper presents FLARE, a feature-based lightweight aggregation for robust evaluation of IoT intrusion detection to address the challenges of...
Plug-and-Play Versatile Compressed Video Enhancement
As a widely adopted technique in data transmission, video compression effectively reduces the size of files, making it possible for real-time cloud computing. However, it comes at the cost of visual quality, posing challenges to the robustness of downstream vision models. In...
Multimodal Large Language Models for Enhanced Traffic Safety: A Comprehensive Review and Future Trends
Traffic safety remains a critical global challenge, with traditional Advanced Driver-Assistance Systems (ADAS) often struggling in dynamic real-world scenarios due to fragmented sensor processing and susceptibility to adversarial conditions. This paper reviews the transformative potential of Multimodal Large Language Models (MLLMs) in...