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We study a model-free federated linear quadratic regulator (LQR) problem where M agents with unknown, distinct yet similar dynamics collaboratively learn an optimal policy to minimize an average quadratic cost while keeping their data private. To exploit the similarity of the agents' dynamics, we propose to use federated learning (FL) to allow the agents to periodically communicate with a central server to train policies by leveraging a larger dataset from all the agents. With this setup, we seek to understand the following questions: (i) Is the learned common policy stabilizing for all agents? (ii) How close is the learned common policy to each agent's own optimal policy? (iii) Can each agent learn its own optimal policy faster by leveraging data from all agents? To answer these questions, we propose a federated and model-free algorithm named FedLQR. Our analysis overcomes numerous technical challenges, such as heterogeneity in the agents' dynamics, multiple local updates, and stability concerns. We show that FedLQR produces a common policy that, at each iteration, is stabilizing for all agents. We provide bounds on the distance between the common policy and each agent's local optimal policy. Furthermore, we prove that when learning each agent's optimal policy, FedLQR achieves a sample complexity reduction proportional to the number of agents M in a low-heterogeneity regime, compared to the single-agent setting. 

Ecosystem conservation is fundamental to guarantee the survival of endangered species and to preserve other ecological functions important for human systems (e.g., water). Planning land conservation increasingly requires a landscape approach to mitigate the negative impacts of spatial threats such as urbanization, agricultural development, and climate change. In this context, landscape connectivity and compactness are vital characteristics for the effective functionality of conservation areas. Connectivity allows species to travel across landscapes, facilitating the flow of genes across populations from different protected areas. Compactness measures the spatial dispersion of protected sites, which can be used to mitigate risk factors associated with species leaving and reentering the reserve. This research describes an optimization model for the design of conservation areas, while inducing connectivity and compactness. We use the Reocks index, a metric of compactness that maximizes the ratio of area of the selected patches to the area of their smallest circumscribing circle. Our model includes budget and minimum protected area constraints to reflect realistic financial and ecological requirements. The initial nonlinear model is reformulated into a mixed-integer linear program, which is solved using an adaptation of the Newtons method for problems with integer variables. We characterize an optimal solution and derive cuts to improve the model performance. We illustrate our results using real life landscapes with irregular patches. 

We initiate the study of federated reinforcement learning under environmental heterogeneity by considering a policy evaluation problem. Our setup involves agents interacting with environments that share the same state and action space but differ in their reward functions and state transition kernels. Assuming agents can communicate via a central server, we ask: Does exchanging information expedite the process of evaluating a common policy? To answer this question, we provide the first comprehensive finite-time analysis of a federated temporal difference (TD) learning algorithm with linear function approximation, while accounting for Markovian sampling, heterogeneity in the agents' environments, and multiple local updates to save communication. Our analysis crucially relies on several novel ingredients: (i) deriving perturbation bounds on TD fixed points as a function of the heterogeneity in the agents' underlying Markov decision processes (MDPs); (ii) introducing a virtual MDP to closely approximate the dynamics of the federated TD algorithm; and (iii) using the virtual MDP to make explicit connections to federated optimization. Putting these pieces together, we rigorously prove that in a low-heterogeneity regime, exchanging model estimates leads to linear convergence speedups in the number of agents. 

We revisit the implementation of a two-qubit entangling gate, the Mølmer-Sørensen gate, using the adiabatic Rydberg dressing paradigm. We study the implementation of rapid adiabatic passage using a two-photon transition, which does not require the use of an ultra-violet laser, and can be implemented using only amplitude modulation of one field with all laser frequencies fixed. We find that entangling gate fidelities, comparable to the one-photon excitation, are achievable with the two-photon excitation. Moreover, we address how the adiabatic dressing protocol can be used to implement entangling gates outside the regime of a perfect Rydberg blockade. We show that using adiabatic dressing we can achieve a scaling of gate fidelity set by the fundamental limits to entanglement generated by the Rydberg interactions while simultaneously retaining limited population in the doubly excited Rydberg state. This allows for fast high fidelity gates for atoms separated beyond the blockade radius. 

This presentation reports different methods of making gallium-based liquid metal (LM) microfluidics passive frequency selective surfaces (FSS). In the first method Si wafer was dry-etched to form a mold and PDMS was replicated from the Si mold to create microfluidic channels with 5x5 array of 300μm width and 200 μm height for Jerusalem cross bars structure, surrounded by four fixed 2 x 1 x 0.2 mm structures. A PDMS lid having 1 mm diameter holes obtained from SLA 3D printed pillar array was aligned and bonded to the replicated PDMS to create sealed microfluidic channels. The bonded structure was placed with lid upwards in an open top 3D printed container measuring 64mm x 64mmarea and 25 mm height. LM was flooded into the container and loaded in Temescal e-beam evaporator at atmospheric pressure. Pressure in evaporator was dropped to 5.75 x 10-6Torr. After a vacuum period of 2 hours LM filling takes place in microfluidic structures because of positive pressure differential introduced by atmospheric pressure. In second method 70 μmthick SU8-2075 stencil consisting of a patterned 1x1 array of see-through FSS structure of above-mentioned dimensions was released from oxidized Si wafer using7:1 BOE. The SU8-2075 stencil was placed over a partially cured PDMS. After complete PDMS curing, an airbrush filled with LM operating at 36 psi with spraying time of less than 5 seconds, placed 4-5 cm over the stencil yields the patterned 1x1 FSS structure after removal of SU8-2075. 

The direct search for dark matter in the form of weakly interacting massive particles (WIMP) is performed by detecting nuclear recoils produced in a target material from the WIMP elastic scattering. The experimental identification of the direction of the WIMP-induced nuclear recoils is a crucial asset in this field, as it enables unmistakable modulation signatures for dark matter. The Recoil Directionality (ReD) experiment was designed to probe for such directional sensitivity in argon dual-phase time projection chambers (TPC), that are widely considered for current and future direct dark matter searches. The TPC of ReD was irradiated with neutrons at the INFN Laboratori Nazionali del Sud. Data were taken with nuclear recoils of known directions and kinetic energy of 72 keV, which is within the range of interest for WIMP-induced signals in argon. The direction-dependent liquid argon charge recombination model by Cataudella et al. was adopted and a likelihood statistical analysis was performed, which gave no indications of significant dependence of the detector response to the recoil direction. The aspect ratioRof the initial ionization cloud is$$R < 1.072$$$R<1.072$with 90 % confidence level.

 

A search for the nonresonant production of Higgs boson pairs in the$HH\to b\overline{b}{\tau }^{+}{\tau }^{-}$channel is performed using$140{\mathrm{fb}}^{-1}$of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. The analysis strategy is optimized to probe anomalous values of the Higgs boson self-coupling modifier${\kappa }_{\lambda }$and of the quartic$HHVV$($V=W,Z$) coupling modifier${\kappa }_{2V}$. No significant excess above the expected background from Standard Model processes is observed. An observed (expected) upper limit${\mu }_{HH}<5.9(3.3)$is set at 95% confidence-level on the Higgs boson pair production cross section normalized to its Standard Model prediction. The coupling modifiers are constrained to an observed (expected) 95% confidence interval of$-3.1<{\kappa }_{\lambda }<9.0$($-2.5<{\kappa }_{\lambda }<9.3$) and$-0.5<{\kappa }_{2V}<2.7$($-0.2<{\kappa }_{2V}<2.4$), assuming all other Higgs boson couplings are fixed to the Standard Model prediction. The results are also interpreted in the context of effective field theories via constraints on anomalous Higgs boson couplings and Higgs boson pair production cross sections assuming different kinematic benchmark scenarios.

© 2024 CERN, for the ATLAS Collaboration2024CERN 

A search for leptoquark pair production decaying into$$te^- \bar{t}e^+$$$t{e}^{-}\overline{t}{e}^{+}$or$$t\mu ^- \bar{t}\mu ^+$$$t{\mu }^{-}\overline{t}{\mu }^{+}$in final states with multiple leptons is presented. The search is based on a dataset ofppcollisions at$$\sqrt{s}=13~\text {TeV} $$$\sqrt{s}=13\text{TeV}$recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb$$^{-1}$$$_{}^{-1}$. Four signal regions, with the requirement of at least three light leptons (electron or muon) and at least two jets out of which at least one jet is identified as coming from ab-hadron, are considered based on the number of leptons of a given flavour. The main background processes are estimated using dedicated control regions in a simultaneous fit with the signal regions to data. No excess above the Standard Model background prediction is observed and 95% confidence level limits on the production cross section times branching ratio are derived as a function of the leptoquark mass. Under the assumption of exclusive decays into$$te^{-}$$$t{e}^{-}$($$t\mu ^{-}$$$t{\mu }^{-}$), the corresponding lower limit on the scalar mixed-generation leptoquark mass$$m_{\textrm{LQ}_{\textrm{mix}}^{\textrm{d}}}$$$m_{{\text{LQ}}_{\text{mix}}^{\text{d}}}$is at 1.58 (1.59) TeV and on the vector leptoquark mass$$m_{{\tilde{U}}_1}$$$m_{{\tilde{U}}_1}$at 1.67 (1.67) TeV in the minimal coupling scenario and at 1.95 (1.95) TeV in the Yang–Mills scenario.