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At least 73 records · Page 4

Multi-millijoule hollow-core fiber compression of short-wave infrared pulses to a single cycle

Approaches for efficient pulse compression can enable dramatic increases in the available peak power, as well as enable the generation of isolated attosecond X-ray pulses. Achieving high compression ratios for longer wavelength drivers has, however, been challenging. We present the compression of few-cycle 2.1 µm central wavelength short-wave infrared laser pulses to 6.9 fs with 2.35 mJ pulse energy at a 10 kHz repetition rate. Electric field resolved measurements reveal a single cycle light field oscillation. With a carrier-envelope-phase stability of 131 mrad and average power fluctuations below 1 %, the system constitutes an excellent light source for strong-field experiments and attosecond physics.

Blöchl, Johannes [Ludwig Maximilian Univ. of Munic↗

Load Control for Frequency Response - A Literature Review

As electricity grids employ greater fractions of renewable energy, which introduce additional variability and uncertainty in the net load, balancing electrical load and generation becomes more challenging. This paper reviews the literature documenting physical simulations and real systems that employ load control (LC) for frequency response and other grid services, which balance net load on the grid and prevent unwanted frequency excursions. Apart from academic and simulation studies, few sources exist on large-scale laboratory hardware testing or actual real-world systems that employ LC for frequency response, and we review them here. Four types of systems that we consider are: 1) Laboratory-based LC experiments, 2) Isolated microgrids that employ LC, 3) Larger grids that employ LC and 4) vehicle-to-grid (V2G) technology, using electric vehicles (EVs). In general, these systems have successfully used LC to meet their objectives, which are often keeping grid frequency within a required band. However, LC struggled to balance grid frequency in an isolated system powered by a single wind turbine, and V2G technology requires refinement in communication and control to provide optimal regulation that adheres to industry standards. As LC grows in the energy industry, we have three main recommendations: 1) encouraging system operators who use LC to publish system characteristics and lessons learned; 2) transitioning more LC theoretical/simulated systems to physical experiments, and physical experiments to real-world pilot systems; 3) demonstrating load control to support isolated, high-wind-contribution systems.

17 WIND ENERGY↗

Application of Quantum Machine Learning to High Energy Physics Analysis at LHC Using Quantum Computer Simulators and Quantum Computer Hardware

Machine learning enjoys widespread success in High Energy Physics (HEP) analyses at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analyses at HL-LHC, and can be a new computational paradigm for big data analyses in High Energy Physics.We have successfully employed three methods (1) Variational Quantum Classifier (VQC) method, (2) Quantum Support Vector Machine Kernel (QSVM-kernel) method and (3) Quantum Neural Network (QNN) method for two LHC flagship analyses: ttH (Higgs production in association with two top quarks) and H->mumu (Higgs decay to two muons, the second generation fermions). We shall address the progressive improvements in performance from method (1) to method (3).We will present our experiences and results of a study on LHC High Energy Physics data analyses with IBM Quantum Simulator and Quantum Hardware (using IBM Qiskit framework), Google Quantum Simulator (using Google Cirq framework), and Amazon Quantum Simulator (using Amazon Braket cloud service). The work is in the context of a Qubit platform (a gate-model quantum computer). Taking into account the present limitation of hardware access, different quantum machine learning methods are studied on simulators and the results are compared with classical machine learning methods (BDT, classical Support Vector Machine and classical Neural Network). Furthermore, we do apply quantum machine learning on IBM quantum hardware to compare performance between quantum simulator and quantum hardware. The work is performed by an international and interdisciplinary collaboration with the Department of Physics and Department of Computer Sciences of University of Wisconsin, CERN Quantum Technology Initiative, IBM Research Zurich, IBM T.J. Watson Research Center, Fermilab Quantum Institute, BNL Computational Science Initiative, State University of New York at Stony Brook, and Quantum Computing and AI Research of Amazon Web Services. This work pioneers a close collaboration of academic institutions with industrial corporations in the High Energy Physics analyses effort. Though the size of event samples in future HL-LHC physics and the limited number of qubits pose some challenges to the Quantum Machine learning studies for High Energy Physics, more advanced quantum computers with larger number of qubits, reduced noise and improved running time (as envisioned by IBM and Google) may outperform classical machine learning in both classification power and in speed.Although the era of efficient quantum computing may still be years away, we have made promising progress and obtained preliminary results in applying quantum machine learning to High Energy Physics. A PROOF OF PRINCIPLE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Effect of cross-beam energy transfer on target-offset asymmetry in direct-drive inertial confinement fusion implosions

The unintentional mispositioning of inertial confinement fusion (ICF) capsules from the center of laser beam convergence has long been shown in simulations to generate large ℓ = 1 asymmetry and significantly degrade implosion symmetry and fusion yields. Experimental yields on the OMEGA Laser System, however, have shown much less sensitivity to this initial target offset. This paper presents simulations of offset ICF implosions improved by including a physics model of cross-beam energy transfer (CBET), a mechanism of laser energy scattering from one beam to another. Room-temperature OMEGA implosion experiments with prescribed target offsets are simulated with and without CBET, illustrating that CBET mitigates the ℓ = 1 implosion asymmetry from target offset. Comparison of simulations to multiple complementary experimental observables indicates the addition of CBET physics in offset simulations is necessary to match experimental results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Magnetic Field Determination for Run 1 of the Fermilab Muon $g-2$ Experiment

The muon $g-2$ experiment at Fermilab aims to measure the anomalous magnetic moment of the muon, $a_{\mu}$, to a precision of 140 parts per billion (ppb). The measurement will shed light on the current $>$3$\sigma$ deviation between Standard Model calculations and the previous measurement made at Brookhaven National Laboratory, either resolving the discrepancy or confirming it to $>$5$\sigma$. In the muon $g-2$ experiment, muons are stored in a magnetic storage ring and their decays are observed. In order to reach the precision goal, the magnetic field experienced by the muons must be known with an uncertainty of \SI{70}{ppb} or less. To this end, the magnetic field was shimmed to unprecedented homogeneity. Two measurement systems are used to track the evolution of the magnetic field. This dissertation describes the motivations for the $g-2$ experiment, gives a brief overview of the experimental principles, introduces the magnetic field measurement hardware, describes the magnetic field shimming process, and presents an analysis of the magnetic field tracking for data collected in spring 2018 during run 1 of the Fermilab muon $g-2$ experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Perform Design Support with MCNP for New Measurements

This report incorporates our work carried out during our 5-month internship at LANL under an internship agreement with EAMEA (École des Applications Militaires de l’Énergie Atomique). After outlining the context in which we worked, we present our work as aid to modeling and predicting the neutronic behavior of nuclear systems, with a view to carrying out criticality experiments qualifying the MCNP code as part of innovative projects. Fourth generation reactors will enable to tackle a lot of issues such as environmental crisis, affordable energy access, and nuclear waste management. They seem to be one of the keys for a sustainable future. Most of the projects that emerge nowadays include the use of HALEU (high assay low enriched uranium) or MOX recycled fuels. Our projects are part of this dynamic and addresses concrete scientific research issues in the nuclear field. Studies of HALEU package are essential to anticipate the need, therefore the Optimus L (OPTImal Modular Universal Shipping cask technology) designed by NAC (Nuclear Assurance Corporation) international but filled with 20 % enriched uranium dioxide (UO 2 ) will be studied to support safe transportation. However, it seems there is no benchmark with a high correlation with the combination of this fuel and this package to validate MCNP simulations. As such, the study will focus on the development of new criticality safety benchmarks for this case. On the other hand, there is a great need for critical benchmarks in the intermediate energy range with MOX fuel. An IER (Integral Experiment Request) has then be requested to answer it through a partnership between French institution IRSN and U.S. Department of Energy's Nuclear Criticality Safety Program (NCSP). This experience planned for 2025 requires to gather calculated data through a MCNP model to be realized safely. Finally, a presentation of our one-week experience at the DAF as part of our discovery of criticality experiments will be introduced in Appendix 1: Week at the DAF (Device Assembly Facility)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Manipulating and Probing Ultrafast Atomic and Molecular Dynamics (Final Report)

This program has focused on the exploration and control of dynamics in atoms, small molecules, clusters, and micro- or nano-structures following ultrafast excitation and/or driven by strong oscillating fields. In our principal experiments, gas phase atoms and molecules were exposed to short pulses of electromagnetic radiation with frequencies ranging from THz into the XUV spectral regions, and with durations from picoseconds to attoseconds. The pulses coherently induce and/or probe dynamics in the electronic, vibrational, and rotational degrees of freedom of the targets. The overarching goal of the various projects has been to exploit strong-field processes and/or implement novel ultrafast techniques for manipulating and probing coherent electronic and nuclear motion. Typically, the relevant system evolution occurs over attosecond to picosecond timescales. In doing so, we have gained a more complete picture of correlated multi-particle dynamics in atoms, molecules, and other complex systems and expanded the toolbox of useful techniques for manipulating and probing those dynamics. Grant funds were primarily used to: (i) pay salaries and fringe benefits for the PI and postdocs and stipends, tuition, and health care costs for graduate students; (ii) cover travel expenses for the PI, postdocs, and students to attend and participate in professional meetings, conferences, and workshops; and (iii) purchase research materials, supplies, and equipment required for experiments. The research resulted in the publication of 24 peer reviewed articles (including 1 in Nature Physics, 2 in Nature Communications, 7 in Physical Review Letters, and 12 in Physical Review A), and 4 PhD dissertations. The specific results from different funding periods are summarized separately in the main report.

74 ATOMIC AND MOLECULAR PHYSICS↗

Development of Large Area µRWELL Detectors for CLAS12 High Luminosity Upgrade at Jefferson Lab

The high-luminosity upgrade of the CEBAF Large Acceptance Spectrometer (CLAS12) will significantly enhance the physics reach of experiments in Hall B at JLab. However, at the current luminosity of L = 1 × 1035 cm-2 s-1, the reconstruction efficiency of charged particles in the forward region of the CEBAF Large Acceptance Spectrometer (CLAS12) is at the level of 85% and limited in part by the drift chambers inability to handle high occupancy, in the first tracking region (DC-R1) of the Forward Detector. The reconstruction efficiency is expected to drop even lower at higher luminosities with the current tracking technology. Various options under consideration to achieve the desired performance at a higher luminosity of L = 2 × 1035 cm-2 s-1 include the addition of fast tracking layers to complement DC-R1 or the replacement of DC-R1 with a different tracking detector technology altogether. In either case, a novel generation of compact, simple and robust Micro-Pattern Gaseous Detector (MPGD) known as the Resistive Micro-Well detector (µRWELL) is the ideal candidate to satisfy the requirements in terms of timing O (10 ns) and position O (100 µm) resolutions. A large µRWELL prototype, combined with a two-dimensional U-V strip readout layer based on the novel concept of capacitive-sharing approach has been developed as a proof of principle for fast tracking capabilities in the forward region of CLAS12 high-luminosity upgrade. In this talk, we will present the technical aspects of the design choices of the large µRWELL prototype under development and report on the detector assembly process and preliminary performance characteristic tests. We will also discuss the plans for the test and characterization of the prototype in beam during spring 2023 CEBAF run. Finally, we will report on ongoing R&D efforts on small prototypes with the goal to improve rate capability, spatial resolution performance and minimize material thickness.

Gnanvo, Kondo↗

Conformal Hierarchical Simulation-Based Inference with Local Validity

Trustworthy and interpretable uncertainty quantification is a long-standing challenge in artificial intelligence. Simulation-based inference (SBI) comprises a broad swath of approaches for estimating latent parameters with uncertainties. Although flexible neural density estimators in SBI can be remark- ably expressive capturing highly structured, high-dimensional posteriors their credible regions can be badly mis-calibrated and are often only accompanied by heuristic coverage checks. We present the first SBI framework that delivers finite-sample local valid coverage guarantees that hold in the neighborhood of each observation. Our framework can couple any off-the-shelf hierarchical SBI engine with a confor- mal Bayesian post-processing step that operates on the posterior predictive density. A kernel-weighted conformity score adapts the conformal quantile to the local geometry of the data, yielding prediction sets that are simultaneously (i) marginally calibrated, (ii) locally valid, and (iii) hierarchical, handling global and observation-specific parameters in a single pass. Through experiments on synthetic data and benchmarks from neuroscience and physics, we show that our approach attains 1 − α coverage, where prior SBI methods under- or over-cover. Our approach also maintains a competitive, credible set size with minimal computational overhead. Finally, our approach can be used to make predictions on real data and give valid credible regions modulo weight-initialization-based model mis-specification.

Trivedi, Shubhendu [Fermilab]↗

A data-driven method to estimate the antiproton background in the Mu2e experiment

The Mu2e experiment at Fermilab will search for the Charged Lepton Flavour Violating (CLFV) process of coherent, neutrinoless µ− → e − conversion in the field of an aluminum nucleus. The expected signal is a monochromatic electron with the energy of 104.97 MeV, slightly below the muon rest mass. Observation of a CLFV process would provide unambiguous evidence for Beyond the Standard Model (BSM) physics. Mu2e is sensitive to a wide range of BSM models and has the capability to distinguish between them, guiding us towards the most accurate models. The key features of the Mu2e experiment are: (1) a high intensity pulsed negative muon beam with about 1010 stopped µ −/s, and (2) a sophisticated superconducting solenoid system with a gradient magnetic field to form and guide the intense muon beam to the target. The Mu2e physics data taking is expected to begin in 2027. For Run I, the expected 5σ discovery sensitivity is Rµe = 1.2 × 10−15, with a total expected background of 0.11 ± 0.03 events. In the absence of a signal, the expected upper limit is Rµe < 6.2 × 10−16 at 90% CL. The success of this experiment hinges on the accurate estimation of the background from various SM processes that could provide signal-like electrons. One of the background processes is antiprotons annihilating in the stopping target to produce signal like electrons through π0 → γγ decays followed by γ conversions, and π− → µ−ν¯ decays followed by µ− decay. It is a relatively small background with large uncertainty (100%) due to the lack of antiproton production cross section information for the Mu2e proton beam energy of 8 GeV. We have developed a novel methodology to estimate the antiproton background in-situ. This forms the main theme of the thesis. We observed that at Mu2e energies, antiproton annihilation in the stopping target is the only source of events with multiple, simultaneous particle trajectories. From Geant4 simulations, only about 0.2% of the simulated antiproton annihilation events have a signal-like electron. Meanwhile, ∼ 5% of events have multiple reconstructible particle tracks per event. Therefore, we have devised a methodology to reconstruct the multi-track events and estimate the antiproton background by exploiting the large ratio of the production rates of the two final states.

Chithirasreemadam, Namitha [Pisa U.] (ORCID:000000↗

High Energy Density Physics of Inertial Confinement Fusion Ablator Materials

The historic December 5, 2022 experiment at Lawrence Livermore National Lab’s (LLNL) National Ignition Facility (NIF) reached fusion energy ignition for the first time. This is the most important scientific breakthrough of the 21st century paves the way to future clean inertial fusion energy (IFE). The diamond (high density carbon (HDC)) ablator material used in this experiment displays detrimental effects due to the development of hydrodynamic instabilities at the diamond/fuel interface under shock compression. New alternatives to diamond ablators are required to step up the energy yield in ICF experiments. The unique combination of mechanical strength (approaching that of diamond), the ability to accommodate high-Z dopants (in contrast to diamond), and the tunability of the properties (through synthesis material with varying sp 3 content) make amorphous carbon (a-C) a promising material for next-generation IFE ablative capsules. However, despite its critical importance to the IFE program, the behavior of a-C carbon at extreme temperatures and pressures remains largely unexplored. The primary goals of this project were to perform groundbreaking dynamic compression experiments and predictive simulations to uncover the fundamental high-energy-density physics of amorphous carbon. Our goals were (1) to uncover the metastability range of amorphous carbon and probe phase transitions to diamond or metastable supercooled liquid carbon; (2) to acquire high-quality equation of state (EOS) data and develop an experimentally validated EOS from machine-learning MD simulations of the complex states of carbon; and (3) to uncover the complex behavior of carbon liquid in both thermodynamically stable and metastable supercooled states by accessing large areas of carbon phase diagram with amorphous samples with variable sp 3 content. Our proposed experimental program included measurements of equation of state and diffraction measurements using the Omega EP laser at the Laboratory of Laser Energetics at the University of Rochester. The theoretical/simulation program involved the development of machine-learning models of the complex response of amorphous carbon under dynamic compression by performing molecular dynamics simulations at experimental time and length scales using leadership class DOE supercomputers. Simulations guided experiments to observe predicted phenomena and acquire critical experimental data in specific pressure-temperature domains to validate theoretical models. This research delivered fundamental properties of novel amorphous carbon IFE ablator material, including phase diagram and EOS. These results will aid in IFE target design and implosion experiments. A unique combination of predictive simulations and dynamic and static experiments provided a highly inspirational intellectual environment for graduate students and postdocs involved in this project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Summary Report Of The FY25 Reactor Physics Verification And Validation Exercises In The Advanced Reactor Technologies - Gas-cooled Reactor Program

Valdiation and verification of numerical tools is critical for ensuring reasonable predictions for design scoping, licensing, and safety analsyis. In this report, two reactor physics verification and validation exercises are presented. The first of these exercises focuses on burnup analysis with data from the Advanced Gas Reactor (AGR) program. Simulations are performed with Monte Carlo N-Particle (MCNP) and are compared with the experimental measurements for the AGR 1 and 2 experiments that utilize both UCO and UO2 fuel. The second exercises utilizes data from the HTR-Proteus experiments to perform reactor physics validation. Specifications of the experimental facility are provdied, along with a demonstration of initial modeling efforts in Serpent for one of the determistic packing experiments. Both cases are part of the Generation-IV international forum (GIF) Very High-Temperature Reactor (VHTR) Computational Methods, Validation, and Benchmarking (CMVB) program, an international collaborative organization dedicated to the verification and validation of High-Temperature Gas-Cooled Reactor (HTGR) analysis. Participation in the CMVB allows the US Department of Energy (DOE) to leverage these existing validation activities to provide extra value through benchmarking activities with other CMVB members.

and Benchmarking (CMVB) program↗

Glass-fiber-reinforced polymeric film as an efficient protecting layer for stable Li metal electrodes

With numerous reports on protecting films for stable lithium (Li) metal electrodes, the key attributes for how to construct these efficient layers have rarely been fully investigated. Here, we report a rationally designed hybrid protective layer (HPL) with each component aligning with one key attribute; i.e., cross-linked poly(dimethylsiloxane) (PDMS) enhances flexibility, polyethylene glycol (PEG) provides homogeneous ion-conducting channels, and glass fiber (GF) affords mechanical robustness. A significant improvement of the electrochemical performance of HPL-modified electrodes can be achieved in Li/HPL@Cu half cells, HPL@Li/HPL@Li symmetric cells, and HPL@Li/LiFePO 4 full cells. Even with an industrial standard LiFePO 4 cathode (96.8 wt % active material), the assembled cell still exhibits a capacity retention of 90% after 100 cycles at 1 C. More importantly, the functionality of each component has been studied comprehensively via electrochemical and physical experiments and simulations, which will provide useful guidance on how to construct efficient protective layers for next-generation energy storage devices.

25 ENERGY STORAGE↗

μRWELL detector developments at Jefferson Lab for high luminosity experiments

One of the future plans at Jefferson Lab is running electron scattering experiments with large acceptance detectors at luminosities > 10^37 cm^−2 s^−1. These experiments allow the measurements of the Double Deeply Virtual Compton Scattering (DDVCS) reaction, an important physics process in the formalism of Generalized Parton Distributions, which has never been measured because of its small cross-section. The luminosity upgrade of CLAS12 or the SOLID detector makes Jefferson Lab a unique place to measure DDVCS. One of the important components of these high luminosity detectors is a tracking system that can withstand high rates of ≈ 1MHz/cm2. The recently developed Micro-Resistive Well (𝜇RWELL) detector technology is a promising option for such a tracking detector by combining good position resolutions, low material budget with simple mechanical construction, and low production costs. In this proceeding, we will discuss recent developments and studies with 𝜇RWELL detectors at Jefferson Lab for future upgrades of the CLAS12 detector to study the DDVCS reaction.

Hauenstein, Florian↗

PERLE - ERL Test Facility at Orsay

PERLE (Powerful ERL for Experiments)[1] is a novel Energy Recovery Linac (ERL) test facility, designed to validate choices for a 50 GeV ERL foreseen in the design of the Large Hadron Electron Collider (LHeC) and the Future Circular Collider (FCC-eh), and to host dedicated nuclear and particle physics experiments. Its main thrust is to probe high current, continuous wave (CW), multi-pass operation with superconducting cavities at 802 MHz. With very high transient beam power (10 MW), PERLE offers an opportunity for controllable study of every beam dynamic effect of interest in the next generation of ERL design and becomes a ‘stepping stone’ between present state-of-art 1 MW ERLs and future 100 MW scale applications.

Bogacz, S. Alex↗

ANS Winter 2022: ATF-2C Physics Safety and Scoping Analysis

ATF-2C comprises four tiers with six rodlets each. The experiment test train (TT) is situated in Loop 2A in the center flux trap (CFT) of the ATR, in which typical pressurized water reactor (PWR) conditions shall be approximated. Tier 1 (bottom) of the TT tests Framatome silicon carbide (SiC) cladding, containing molybdenum heater rods. Low-enriched uranium (LEU) Framatome rodlets with chrome-coated M5 cladding have been modeled in their place for the physics safety analysis to allow the substitution of this tier with fuel if needed. Tier 2 tests LEU Framatome rodlets with M5 cladding, which had irradiated in ATR in prior ATF experiments. Tier 3 tests General Atomics SiC composite cladding, also containing molybdenum heater rods. Tier 4/5/6 (top) tests the Japan Atomic Energy Agency (JAEA)/Mitsubishi Heavy Industries (MHI) fueled rodlets. This upper tier tests LEU rodlets with chrome-coated MDA cladding—several with temperature or pressure instrumentation. To flatten the axial power profile, lower portion of Tier 4/5/6 is surrounded by a hafnium (Hf) shroud, and the bottom two UO2 pellets are of natural enrichment. The ATF-2C TT is to be irradiated in the CFT of ATR (Fig. 1) for three or four 60-day cycles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Exotic Meson Photoproduction at GlueX – Search for the hybrid candidate Y

Understanding the hadron spectrum is one of the primary goals of non-perturbative QCD. Many predictions have experimentally been confirmed, others still remain under experimental investigation. Of particular interest is how gluonic excitations give rise to states with constituent glue. One class of such states are hybrid mesons that are predicted by theoretical models and Lattice QCD calculations. Searching for and understanding the nature of these states is a primary physics goal of the GlueX experiment at the CEBAF accelerator at Jefferson Lab. A search for a JPC = 1-- hybrid meson candidate, the Y (2175), in phi(1020)pi+pi+ and phi(1020)f0(980) channels in photoproduction on a proton target has been conducted. A first measurement of non-resonant phi(1020)pi+pi+ and phi(1020)f0(980) total cross sections in photoproduction has been performed. An upper limit on the resonance production cross section for the Y (2175) -> phi(1020)pi+pi+ and Y (2175) -> phi(1020)f0(980) channels are estimated. Since the analysis essentially depends on the quality of the charged kaon identification, also an optimization of particle identification through an improvement of the energy loss estimation in the CDC by a truncated mean method has been investigated.

Hamdi, Abdennacer↗

Minimal one-dimensional model of bad metal behavior from fast particle-hole scattering

A strongly interacting plasma of linearly dispersing electron and hole excitations in two spatial dimensions (2D), also known as a Dirac fluid, can be captured by relativistic hydrodynamics and shares many universal features with other quantum critical systems. Here, we propose a one-dimensional (1D) model to capture key aspects of the 2D Dirac fluid while including lattice effects and being amenable to nonperturbative computation. When interactions are added to the Dirac-like 1D dispersion without opening a gap, we show that this kind of irrelevant interaction is able to preserve Fermi-liquid-like quasiparticle features while relaxing a zero-momentum charge current via collisions between particle-hole excitations, leading to resistivity that is linear in temperature via a mechanism previously discussed for large-diameter metallic carbon nanotubes. We further provide a microscopic lattice model and obtain numerical results via density-matrix renormalization group simulations, which support the above physical picture. The limits on such fast relaxation at strong coupling are of considerable interest because of the ubiquity of bad metals in experiments.

1-dimensional systems↗