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Self-organization in an unmagnetized collisionless plasma (in this paper) refers to formation of transient coherent structures such as collective oscillations (electrostatic waves) or magnetic fields resulting from so-called kinetic effects in the plasma. This topical review provides a comprehensive analysis of the self-organization of strong-field photoionized, non-equilibrium plasmas through kinetic instabilities. The authors propose and demonstrate a novel experimental platform that enables the formation of dense plasmas with known highly anisotropic and non-thermal electron velocity distribution functions on a timescale on the order of an inverse electron plasma frequency. We then show that such plasmas are highly susceptible to a hierarchy of kinetic instabilities, including two-stream, current filamentation and Weibel, that convert a fraction of the electron kinetic energy into electric and/or magnetic energy stored in self-organized structures. The electrostatic waves so produced are measured using a collective light (Thomson) scattering technique with femtosecond resolution as the kinetic instabilities aided by collisions eventually thermalize the plasma electrons. In addition, we describe a novel experimental technique that has made it possible to map the temporal evolution of the wavenumber spectrum of the thermal Weibel instability with picosecond resolution, which leads to the formation of quasi-static coherent magnetic fields with different topologies in photoionized plasmas. Finally, the paper summarizes the important results and discusses future directions on this topic.

 

The past decade has seen tremendous progress in the production and utilization of vortex and vector laser pulses. Although both are considered as structured light beams, the vortex lasers have helical phase fronts and phase singularities, while the vector lasers have spatially variable polarization states and polarization singularities. In contrast to the vortex pulses that carry orbital angular momentum (OAM), the vector laser pulses have a complex spin angular momentum (SAM) and OAM coupling. Despite many potential applications enabled by such pulses, the generation of high-power/-intensity vortex and vector beams remains challenging. Here, we demonstrate using theory and three-dimensional simulations that the strongly-coupled stimulated Brillouin scattering (SC-SBS) process in plasmas can be used as a promising amplification technique with up to 65% energy transfer efficiency from the pump beam to the seed beam for both vortex and vector pulses. We also show that SC-SBS is strongly polarization-dependent in plasmas, enabling an all-optical polarization control of the amplified seed beam. Additionally, the interaction of such structured lasers with plasmas leads to various angular momentum couplings and decouplings that produce intense new light structures with controllable OAM and SAM. This scheme paves the way for novel optical devices such as plasma-based amplifiers and light field manipulators.

 

Optical Thomson scattering is now a mature diagnostic tool for precisely measuring local plasma density and temperature. These measurements typically take advantage of a simplified analytical model of the scattered spectrum, which is built upon the assumption that each plasma species is in thermal equilibrium. However, this assumption fails for most laboratory plasmas of interest, which are often produced through high field ionization of atoms via ultrashort laser pulses and vulnerable to several kinetic instabilities. While it is possible to analytically model the Thomson scattered spectrum for some non-Maxwellian distribution functions, it is often not practical to do so for laboratory plasmas with highly complex and unstable distribution functions. We present a new method for predicting the Thomson scattered spectrum from any plasma directly from fully kinetic particle-in-cell simulations. This approach allows us to model the contributions of kinetic instabilities to the Thomson spectrum that aren’t taken into account in Maxwellian theory. We demonstrate this method’s capability to capture nonthermal features in the Thomson spectrum by simulating a simple bumpon- tail plasma as well as a more complex laser-ionized plasma. The versatility of this approach makes it an effective aid in the experimental design of Thomson diagnostics to directly characterize kinetic instabilities in laboratory plasmas. Index Terms—plasma measurement, low-temperature plasmas, plasma diagnostics, plasma simulation, plasma stability, plasma density, plasma temperature 

The origin of the seed magnetic field that is amplified by the galactic dynamo is an open question in plasma astrophysics. Aside from primordial sources and the Biermann battery mechanism, plasma instabilities have also been proposed as a possible source of seed magnetic fields. Among them, thermal Weibel instability driven by temperature anisotropy has attracted broad interests due to its ubiquity in both laboratory and astrophysical plasmas. However, this instability has been challenging to measure in a stationary terrestrial plasma because of the difficulty in preparing such a velocity distribution. Here, we use picosecond laser ionization of hydrogen gas to initialize such an electron distribution function. We record the 2D evolution of the magnetic field associated with the Weibel instability by imaging the deflections of a relativistic electron beam with a picosecond temporal duration and show that the measured k -resolved growth rates of the instability validate kinetic theory. Concurrently, self-organization of microscopic plasma currents is observed to amplify the current modulation magnitude that converts up to ~1% of the plasma thermal energy into magnetic energy, thus supporting the notion that the magnetic field induced by the Weibel instability may be able to provide a seed for the galactic dynamo. 

Absolute density measurements of low-ionization-degree or low-density plasmas ionized by lasers are very important for understanding strong-field physics, atmospheric propagation of intense laser pulses, Lidar etc. A cross-polarized common-path temporal interferometer using balanced detection was developed for measuring plasma density with a sensitivity of ∼0.6 mrad, equivalent to a plasma density-length product of ∼2.6 × 10¹³cm⁻²if using an 800 nm probe laser. By using this interferometer, we have investigated strong-field ionization yield versus intensity for various noble gases (Ar, Kr, and Xe) using 800 nm, 55 fs laser pulses with both linear (LP) and circular (CP) polarization. The experimental results were compared to the theoretical models of Ammosov-Delone-Krainov (ADK) and Perelomov-Popov-Terent’ev (PPT). We find that the measured phase change induced by plasma formation can be explained by the ADK theory in the adiabatic tunneling ionization regime, while PPT model can be applied to all different regimes. We have also measured the photoionization and fractional photodissociation of molecular (MO) hydrogen. By comparing our experimental results with PPT and MO-PPT models, we have determined the likely ionization pathways when using three different pump laser wavelengths of 800 nm, 400 nm, and 267 nm.

 

Datacenter scheduling research often assumes resources as a constant quantity, but increasingly external factors shape capacity dynamically, and beyond the control of an operator. Based on emerging examples, we define a new, open research challenge: the variable capacity resource scheduling problem. The objective here is effective resource utilization despite sudden, perhaps large, changes in the available resources. We define the problem, key dimensions of resource capacity variation, and give specific examples that arise from the natural world (carboncontent, power price, datacenter cooling, and more). Key dimensions of the resource capacity variation include dynamic range, frequency, and structure. With these dimensions, an empirical trace can be characterized, abstracting it from the many possible important real-world generators of variation. Resource capacity variation can arise from many causes including weather, market prices, renewable energy, carbon emission targets, and internal dynamic power management constraints. We give examples of three different sources of variable capacity. Finally, we show variable resource capacity presents new scheduling challenges. We show how variation can cause significant performance degradation in existing schedulers, with up to 60% goodput reduction. Further, initial results also show intelligent scheduling techniques can be helpful. These insights show the promise and opportunity for future scheduling studies on resource volatility. 

Datacenter scheduling research often assumes resources as a constant quantity, but increasingly external factors shape capacity dynamically, and beyond the control of an operator. Based on emerging examples, we define a new, open research challenge: the variable capacity resource scheduling problem. The objective here is effective resource utilization despite sudden, perhaps large, changes in the available resources. We define the problem, key dimensions of resource capacity variation, and give specific examples that arise from the natural world (carbon- content, power price, datacenter cooling, and more). Key dimensions of the resource capacity variation include dynamic range, frequency, and structure. With these dimensions, an empirical trace can be character- ized, abstracting it from the many possible important real-world generators of variation. Resource capacity variation can arise from many causes including weather, market prices, renewable energy, carbon emission targets, and internal dynamic power management constraints. We give examples of three dif- ferent sources of variable capacity. Finally, we show variable resource capacity presents new scheduling challenges. We show how variation can cause significant performance degra- dation in existing schedulers, with up to 60% goodput reduction. Further, initial results also show intelligent scheduling techniques can be helpful. These insights show the promise and opportunity for future scheduling studies on resource volatility. 

Today's serverless provides "function-as-a-service" with dynamic scaling and fine-grained resource charging, enabling new cloud applications. Serverless functions are invoked as a best-effort service. We propose an extension to serverless, called real-time serverless that provides an invocation rate guarantee, a service-level objective (SLO) specified by the application, and delivered by the underlying implementation. Real-time serverless allows applications to guarantee real-time performance. We study real-time serverless behavior analytically and empirically to characterize its ability to support bursty, real-time cloud and edge applications efficiently. Finally, we use a case study, traffic monitoring, to illustrate the use and benefits of real-time serverless, on our prototype implementation.