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Dielectric capillaries are widely used to generate plasmas for plasma wakefield acceleration. When a relativistic drive bunch travels through a capillary with misaligned trajectory with respect to the capillary axis, it is deflected by the effect of the dielectric transverse wakefields it drives. We experimentally show that the deflection effect increases along the bunch and with larger misalignment, and we investigate the decay of dielectric wakefields by measuring the effect on the front of a trailing bunch. We discuss the implications for the design of a plasma wakefield accelerator based on dielectric capillaries., Comment: Proceedings of the 2024 Advanced Accelerator Concepts Workshop

This paper proposes a methodology to solve generation expansion equilibrium problems by using a predictive model to represent the equilibrium in a simplified network constrained electricity market. The investment problem for each generation company (Genco) is a bi-level problem with the investment decision made in the upper level and market clearing condition in the lower level, which traditionally is represented as a Mathematical Program with Equilibrium Constraint (MPEC). The predictive model is trained for estimating the system-wide revenues for each technology type across energy, ancillary services and capacity markets given the amount of technology-specific installed capacity on the grid. The profit maximization investment problem for each Genco is solved using a global search algorithm, which uses the predictive model to evaluate the objective function. To solve for the strategic equilibrium, each Genco's problem is plugged into a diagonalization algorithm that is generally used in multi-leader, single-follower bi-level problems. The methodology presented here enables significant computational improvements while still capturing the desired market characteristics and dynamics of traditional equilibrium modeling approaches

The space-charge field of a relativistic charged bunch propagating in plasma is screened due to the presence of mobile charge carriers. We experimentally investigate such screening by measuring the effect of dielectric wakefields driven by the bunch in a uncoated dielectric capillary where the plasma is confined. We show that the plasma screens the space-charge field and therefore suppresses the dielectric wakefields when the distance between the bunch and the dielectric surface is much larger than the plasma skin depth. Before full screening is reached, the effects of dielectric and plasma wakefields are present simultaneously.

Short-wavelength repulsive potentials for quantum gases allow to realize new systems and to study new phenomena. Here we report the realization of repulsive optical potentials for dysprosium atoms in the blue region of the spectrum, at wavelengths close to 400 nm. We employ a spectrallyfiltered diode laser system to measure both scalar and tensorial components of the polarizability of dysprosium, which we find in good agreement with the theoretical predictions. We demonstrate the implementation of potential strengths appropriate to manipulate Bose-Einstein condensates, with scattering-limited lifetimes exceeding one second. This type of optical potentials opens interesting directions for the study of dipolar superfluids and supersolids., Comment: 7 pages, 8 figures

The development of nanoscale nonlinear elements in photonic integrated circuits is hindered by the physical limits to the nonlinear optical response of dielectrics, which requires that the interacting waves propagate in transparent volumes for distances much longer than their wavelength. Here we present experimental evidence that optical nonlinearities in doped semiconductors are due to free-electron and their efficiency could exceed by several orders of magnitude that of conventional dielectric nonlinearities. Our experimental findings are supported by comprehensive computational results based on the hydrodynamic modeling, which naturally includes nonlocal effects, of the free-electron dynamics in heavily doped semiconductors. By studying third-harmonic generation from plasmonic nanoantenna arrays made out of heavily n-doped InGaAs with increasing levels of free-carrier density, we discriminate between hydrodynamic and dielectric nonlinearities. As a result, the value of maximum nonlinear efficiency as well as its spectral location can now be controlled by tuning the doping level. Having employed the common material platform InGaAs/InP that supports integrated waveguides, our findings pave the way for future exploitation of plasmonic nonlinearities in all-semiconductor photonic integrated circuits.

Recently, a new category of superfluids and superconductors has been discovered in various systems. These could be linked to the idea of a supersolid phase, featuring a macroscopic wavefunction with spatial modulation resulting from simultaneous, spontaneous breaking of gauge and translational symmetries. However, this relation has only been recognized in some cases and there is the need for universal properties quantifying the differences between supersolids and ordinary superfluids/superconductors or crystals. A key property is the superfluid fraction, which measures the reduction in superfluid stiffness due to spatial modulation, leading to the non-standard superfluid dynamics of supersolids. Here we employ the Josephson effect, common in superfluids and superconductors, to measure the superfluid fraction in a supersolid. Even without a physical barrier, the Josephson effect arises spontaneously in a supersolid due to spatial modulation. Individual lattice cells act as self-induced Josephson junctions, allowing the direct determination of the local superfluid fraction. We studied a cold-atom dipolar supersolid, revealing a significant sub-unity superfluid fraction. Our results open new research directions, enabling the exploration of novel phenomena like partially quantized vortices and supercurrents, potentially unifying the understanding of supersolid-like systems, and introducing a new type of Josephson junction., Comment: 15 pages, 10 figures

In multi-timescale multi-agent reinforcement learning (MARL), agents interact across different timescales. In general, policies for time-dependent behaviors, such as those induced by multiple timescales, are non-stationary. Learning non-stationary policies is challenging and typically requires sophisticated or inefficient algorithms. Motivated by the prevalence of this control problem in real-world complex systems, we introduce a simple framework for learning non-stationary policies for multi-timescale MARL. Our approach uses available information about agent timescales to define a periodic time encoding. In detail, we theoretically demonstrate that the effects of non-stationarity introduced by multiple timescales can be learned by a periodic multi-agent policy. To learn such policies, we propose a policy gradient algorithm that parameterizes the actor and critic with phase-functioned neural networks, which provide an inductive bias for periodicity. The framework's ability to effectively learn multi-timescale policies is validated on a gridworld and building energy management environment., Comment: Accepted at IEEE CDC'23. 7 pages, 6 figures

All-optical modulation yields the promise of high-speed information processing. In this frame, metasurfaces are rapidly gaining traction as ultrathin multifunctional platforms for light management. Among the featured functionalities, they enable light wavefront manipulation and, more recently, demonstrated the ability to perform light-by-light manipulation through nonlinear optical processes. Here, by employing a nonlinear periodic metasurface, we demonstrate all-optical routing of telecom photons upconverted to the visible range. This is achieved via the interference between two frequency-degenerate upconversion processes, namely third-harmonic and sum-frequency generation, stemming from the interaction of a pump pulse with its frequency-doubled replica. By tuning the relative phase and polarization between these two pump beams, and concurrently engineering the nonlinear emission of the individual elements of the metasurfaces (meta-atoms) along with its pitch, we route the upconverted signal among the diffraction orders of the metasurface with a modulation efficiency up to 90%. Thanks to the phase control and the ultrafast dynamics of the underlying nonlinear processes, free-space all-optical routing could be potentially performed at rates close to the employed optical frequencies divided by the quality factor of the optical resonances at play. Our approach adds a further twist to optical interferometry, which is a key-enabling technique in a wide range of applications, such as homodyne detection, radar interferometry, LiDAR technology, gravitational waves detection, and molecular photometry. In particular, the nonlinear character of light upconversion combined with phase sensitivity is extremely appealing for enhanced imaging and biosensing., Comment: 18 pages, 6 figures

APEIRON is a framework encompassing the general architecture of a distributed heterogeneous processing platform and the corresponding software stack, from the low level device drivers up to the high level programming model. The framework is designed to be efficiently used for studying, prototyping and deploying smart trigger and data acquisition (TDAQ) systems for high energy physics experiments., Comment: Under review in Journal of Physics: Conference Series (ACAT 2022)

A long-standing goal of machine-learning-based protein engineering is to accelerate the discovery of novel mutations that improve the function of a known protein. We introduce a sampling framework for evolving proteins in silico that supports mixing and matching a variety of unsupervised models, such as protein language models, and supervised models that predict protein function from sequence. By composing these models, we aim to improve our ability to evaluate unseen mutations and constrain search to regions of sequence space likely to contain functional proteins. Our framework achieves this without any model fine-tuning or re-training by constructing a product of experts distribution directly in discrete protein space. Instead of resorting to brute force search or random sampling, which is typical of classic directed evolution, we introduce a fast MCMC sampler that uses gradients to propose promising mutations. We conduct in silico directed evolution experiments on wide fitness landscapes and across a range of different pre-trained unsupervised models, including a 650M parameter protein language model. Our results demonstrate an ability to efficiently discover variants with high evolutionary likelihood as well as estimated activity multiple mutations away from a wild type protein, suggesting our sampler provides a practical and effective new paradigm for machine-learning-based protein engineering., Comment: 31 pages, 8 figures. To appear in the Machine Learning: Science & Technology (ML:S&T) journal. Code is available at https://github.com/pemami4911/ppde. A short version of this work appeared at the NeurIPS 2022 Machine Learning in Structural Biology Workshop

In this article, we share our experience related to the new photo-injector commissioning at the SPARC\_LAB test facility. The new photo-injector was installed into an existing machine and our goal was not only to improve the final beam parameters themselves but to improve the machine handling in day-to-day operations as well. Thus, besides the pure beam characterization, this article contains information about the improvements, that were introduced into the new photo-injector design from the machine maintenance point of view, and the benefits, that we gained by using the new technique to assemble the gun itself.

A timely and long-term programme of kaon decay measurements at a new level of precision is presented, leveraging the capabilities of the CERN Super Proton Synchrotron (SPS). The proposed programme is firmly anchored on the experience built up studying kaon decays at the SPS over the past four decades, and includes rare processes, CP violation, dark sectors, symmetry tests and other tests of the Standard Model. The experimental programme is based on a staged approach involving experiments with charged and neutral kaon beams, as well as operation in beam-dump mode. The various phases will rely on a common infrastructure and set of detectors., Comment: Letter of Intent submitted to CERN SPSC. Address all correspondence to hike-eb@cern.ch

Grid-interactive building control is a challenging and important problem for reducing carbon emissions, increasing energy efficiency, and supporting the electric power grid. Currently researchers and practitioners are confronted with a choice of control strategies ranging from model-free (purely data-driven) to model-based (directly incorporating physical knowledge) to hybrid methods that combine data and models. In this work, we identify state-of-the-art methods that span this methodological spectrum and evaluate their performance for multi-zone building HVAC control in the context of three demand response programs. We demonstrate, in this context, that hybrid methods offer many benefits over both purely model-free and model-based methods as long as certain requirements are met. In particular, hybrid controllers are relatively sample efficient, fast online, and high accuracy so long as the test case falls within the distribution of training data. Like all data-driven methods, hybrid controllers are still subject to generalization errors when applied to out-of-sample scenarios. Key takeaways for control strategies are summarized and the developed software framework is open-sourced.

We provide a theoretical characterization of the dynamical crossing of the superfluid-supersolid phase transition for a dipolar condensate confined in an elongated trap, as observed in the recent experiment by G. Biagioni et al. [Phys. Rev. X 12, 021019 (2022)]. By means of the extended Gross-Pitaevskii theory, which includes the Lee-Huang-Yang quantum fluctuation correction, we first analyze the ground state configurations of the system as a function of the interparticle scattering length, for both trap configurations employed in the experiment. Then, we discuss the effects of the ramp velocity, by which the scattering length is tuned across the transition, on the collective excitations of the system in both the superfluid and supersolid phases. We find that, when the transverse confinement is sufficiently strong and the transition has a smooth (continuous) character, the system essentially displays a (quasi) 1D behavior, its excitation dynamics being dominated by the axial breathing modes. Instead, for shallower transverse trapping, when the transition becomes discontinuous, the collective excitations of the supersolid display a coupling with the transverse modes, signalling the onset of a dimensional crossover., Comment: 9 pages, 8 figures

A new FPGA-based low-level trigger processor has been installed at the NA62 experiment. It is intended to extend the features of its predecessor due to a faster interconnection technology and additional logic resources available on the new platform. With the aim of improving trigger selectivity and exploring new architectures for complex trigger computation, a GPU system has been developed and a neural network on FPGA is in progress. They both process data streams from the Ring Imaging Cherenkov detector of the experiment to extract in real time high level features for the trigger logic. Description of the systems, latest developments and design flows are reported in this paper., Comment: 5 pages, 3 figures, 1 table. Submitted to JINST as part of the TWEPP2021 conference proceeding (Topical Workshop on Electronics for Particle Physics, 20 - 24 September, 2021, online)

The APEnet+ board delivers a point-to-point, low-latency, 3D torus network interface card. In this paper we describe the latest generation of APEnet NIC, APEnet v5, integrated in a PCIe Gen3 board based on a state-of-the-art, 28 nm Altera Stratix V FPGA. The NIC features a network architecture designed following the Remote DMA paradigm and tailored to tightly bind the computing power of modern GPUs to the communication fabric. For the APEnet v5 board we show characterizing figures as achieved bandwidth and BER obtained by exploiting new high performance ALTERA transceivers and PCIe Gen3 compliancy.

We assess experimentally and theoretically the character of the superfluid-supersolid quantum phase transition recently discovered in trapped dipolar quantum gases. We find that one-row supersolids can have already two types of phase transitions, discontinuous and continuous, that are reminiscent of the first- and second-order transitions predicted in the thermodynamic limit in 2D and 1D, respectively. The smooth crossover between the two regimes is peculiar to supersolids and can be controlled via the transverse confinement and the atom number. We justify our observations on the general ground of the Landau theory of phase transitions. The quasi-adiabatic crossing of a continuous phase transition opens new directions of investigation for supersolids., Comment: 15 pages, 15 figures