Generation of stable and breathing flat-top solitons via Raman assisted four wave mixing in microresonators

Flat-top-soliton (or platicon) dynamics in coherently pumped normal dispersion microresonators is important for both fundamental nonlinear physics and microcomb generation in the visible band. Here we numerically investigate the platicon generation that is initiated via Raman assisted four wave mixing instead of mode interaction. To show the possibility of generating coherent combs in the visible band, we design an aluminum nitride (AlN) microresonator with normal dispersion and investigate the comb generation dynamics in simulations. Stable platicon Kerr combs can be generated in this AlN microresonator using a 780-nm pump. Moreover, we also observe a breather platicon dynamics induced by the narrow Raman gain spectrum of crystalline AlN, which shows distinct dynamics from the dark soliton breathers reported in previous work that are dominated by Kerr effect. A phase diagram bearing the influence of the pump detuning and pump power on the breathing dynamics of the breather platicon is also computed. Furthermore, a transition to chaotic breathing is numerically observed

Understanding and Optimizing Serverless Workloads in CXL-Enabled Tiered Memory

Recent Serverless workloads tend to be largescaled/CPU-memory intensive, such as DL, graph applications, that require dynamic memory-to-compute resources provisioning. Meanwhile, recent solutions seek to design page management strategies for multi-tiered memory systems, to efficiently run heavy workloads. Compute Express Link (CXL) is an ideal platform for serverless workloads runtime that offers a holistic memory namespace thanks to its cache coherent feature and large memory capacity. However, naively offloading Serverless applications to CXL brings substantial latencies. In this work, we first quantify CXL impacts on various Serverless applications. Second, we argue the opportunity of provisioning DRAM and CXL in a fine-grained, application-specific manner to Serverless workloads, by creating a shim layer to identify, and naively place hot regions to DRAM, while leaving cold/warm regions to CXL. Based on the observation, we finally propose the prototype of Porter, a middleware in-between modern Serverless architecture and CXL-enabled tiered memory system, to efficiently utilize memory resources, while saving costs

An integrable road to a perturbative plateau

As has been known since the 90s, there is an integrable structure underlying two-dimensional gravity theories. Recently, two-dimensional gravity theories have regained an enormous amount of attention, but now in relation with quantum chaos - superficially nothing like integrability. In this paper, we return to the roots and exploit the integrable structure underlying dilaton gravity theories to study a late time, large $e^{S_\text{BH}}$ double scaled limit of the spectral form factor. In this limit, a novel cancellation due to the integrable structure ensures that at each genus $g$ the spectral form factor grows like $T^{2g+1}$, and that the sum over genera converges, realising a perturbative approach to the late-time plateau. Along the way, we clarify various aspects of this integrable structure. In particular, we explain the central role played by ribbon graphs, we discuss intersection theory, and we explain what the relations with dilaton gravity and matrix models are from a more modern holographic perspective.Comment: 44 pages + appendice

EC^2: Emergent Communication for Embodied Control

Embodied control requires agents to leverage multi-modal pre-training to quickly learn how to act in new environments, where video demonstrations contain visual and motion details needed for low-level perception and control, and language instructions support generalization with abstract, symbolic structures. While recent approaches apply contrastive learning to force alignment between the two modalities, we hypothesize better modeling their complementary differences can lead to more holistic representations for downstream adaption. To this end, we propose Emergent Communication for Embodied Control (EC^2), a novel scheme to pre-train video-language representations for few-shot embodied control. The key idea is to learn an unsupervised "language" of videos via emergent communication, which bridges the semantics of video details and structures of natural language. We learn embodied representations of video trajectories, emergent language, and natural language using a language model, which is then used to finetune a lightweight policy network for downstream control. Through extensive experiments in Metaworld and Franka Kitchen embodied benchmarks, EC^2 is shown to consistently outperform previous contrastive learning methods for both videos and texts as task inputs. Further ablations confirm the importance of the emergent language, which is beneficial for both video and language learning, and significantly superior to using pre-trained video captions. We also present a quantitative and qualitative analysis of the emergent language and discuss future directions toward better understanding and leveraging emergent communication in embodied tasks.Comment: Published in CVPR202