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We address the fundamental task of converting $n$ uses of an unknown unitary transformation into a quantum state (i.e., storage) and later retrieval of the transformation. Specifically, we consider the case where the unknown unitary is selected with equal prior probability from two options. First, we prove that the optimal storage strategy involves the sequential application of the $n$ uses of the unknown unitary, and it produces the optimal state for discrimination between the two possible unitaries. Next, we show that incoherent "measure-and-prepare" retrieval achieves the maximum fidelity between the retrieved operation and the original (qubit) unitary. We then identify the retrieval strategy that maximizes the probability of successfully and perfectly retrieving the unknown transformation. In the regime in which the fidelity between the two possible unitaries is large the probability of success scales as $ P_{succ} = 1 - \mathcal{O}(n^{-2} ) $, which is a quadratic improvement with respect to the case in which the unitaries are drawn from the entire unitary group $U(d)$ with uniform prior probability. Finally, we present an optical experiment for this approach and assess the storage and retrieval quality using quantum tomography of states and processes. The results are discussed in relation to non-optimal measure-and-prepare strategy, highlighting the advantages of our protocol., Comment: 18 pages, 10 figures

Handling heterogeneity and unpredictability are two core problems in pervasive computing. The challenge is to seamlessly integrate devices with varying computational resources in a dynamic environment to form a cohesive system that can fulfill the needs of all participants. Existing work on systems that adapt to changing requirements typically focuses on optimizing individual variables or low-level Service Level Objectives (SLOs), such as constraining the usage of specific resources. While low-level control mechanisms permit fine-grained control over a system, they introduce considerable complexity, particularly in dynamic environments. To this end, we propose drawing from Active Inference (AIF), a neuroscientific framework for designing adaptive agents. Specifically, we introduce a conceptual agent for heterogeneous pervasive systems that permits setting global systems constraints as high-level SLOs. Instead of manually setting low-level SLOs, the system finds an equilibrium that can adapt to environmental changes. We demonstrate the viability of AIF agents with an extensive experiment design, using heterogeneous and lifelong federated learning as an application scenario. We conduct our experiments on a physical testbed of devices with different resource types and vendor specifications. The results provide convincing evidence that an AIF agent can adapt a system to environmental changes. In particular, the AIF agent can balance competing SLOs in resource heterogeneous environments to ensure up to 98% fulfillment rate., Comment: 11 pages, double column, 15 figures, 2 tables

The design of small solenoids without/with-partial insulation among turns or layers has been proven to grant higher thermal stability than for standard insulated cases. This technology implies higher safety standards, by allowing for 1-100 V highest voltage in the single TF coil; at the same time, a passive/simpler quench protection systems (QPS) becomes a concrete opportunity. Besides, experiments and simulations on large-scale solenoids do not guarantee yet the same advantages, as the redistribution of currents after quench is not yet clear and the temperature margins allowed by LTS are narrower. The possibility for full internal energy dissipation is here discussed analytically, highlighting the already high final temperatures being reached and the limits of the held hypotheses. \\ This study presents therefore a new effective 3-D original numerical model, developed for simulating in a fast fashion charge/discharge and quench of a EUROfusion DEMO toroidal field (TF) coil, by coupling both electrical and thermal physics in the same solver. Its structure is explained as well as its first benchmarks. Finally, the first results are reported of a parametric study where only turn-turn localized bridges are considered, discussing the consequences and the future outlook for this simulation work.

The current scenario of IoT is witnessing a constant increase on the volume of data, which is generated in constant stream, calling for novel architectural and logical solutions for processing it. Moving the data handling towards the edge of the computing spectrum guarantees better distribution of load and, in principle, lower latency and better privacy. However, managing such a structure is complex, especially when requirements, also referred to Service Level Objectives (SLOs), specified by applications' owners and infrastructure managers need to be ensured. Despite the rich number of proposals of Machine Learning (ML) based management solutions, researchers and practitioners yet struggle to guarantee long-term prediction and control, and accurate troubleshooting. Therefore, we present a novel ML paradigm based on Active Inference (AIF) -- a concept from neuroscience that describes how the brain constantly predicts and evaluates sensory information to decrease long-term surprise. We implement it and evaluate it in a heterogeneous real stream processing use case, where an AIF-based agent continuously optimizes the fulfillment of three SLOs for three autonomous driving services running on multiple devices. The agent used causal knowledge to gradually develop an understanding of how its actions are related to requirements fulfillment, and which configurations to favor. Through this approach, our agent requires up to thirty iterations to converge to the optimal solution, showing the capability of offering accurate results in a short amount of time. Furthermore, thanks to AIF and its causal structures, our method guarantees full transparency on the decision making, making the interpretation of the results and the troubleshooting effortless.

In the context of autonomous vehicles (AVs), offloading is essential for guaranteeing the execution of perception tasks, e.g., mobile mapping or object detection. While existing work focused extensively on minimizing inter-vehicle networking latency through offloading, other objectives become relevant in the case of vehicle platoons, e.g., energy efficiency or data quality for heavy-duty or public transport. Therefore, we aim to enforce these Service Level Objectives (SLOs) through intelligent task offloading within AV platoons. We present a collaborative framework for handling and offloading services in a purely Vehicle-to-Vehicle approach (V2V) based on Bayesian Networks (BNs). Each service aggregates local observations into a platoon-wide understanding of how to ensure SLOs for heterogeneous vehicle types. With the resulting models, services can proactively decide to offload if this promises to improve global SLO fulfillment. We evaluate the approach in a real-case setting, where vehicles in a platoon continuously (i.e., every 500 ms) interpret the SLOs of three actual perception services. Our probabilistic, predictive method shows promising results in handling large AV platoons; within seconds, it detects and resolves SLO violations through offloading.

High mobility of twin boundaries in modulated martensites of Ni-Mn-Ga-based ferromagnetic shape memory alloys holds a promise for unique magnetomechanical applications. This feature has not been fully understood so far, and in particular it has yet not been unveiled what makes the lattice mechanics of modulated Ni-Mn-Ga specifically different from other martensitic alloys. Here, results of dedicated laser-ultrasonic measurements on hierarchically twinned five-layer modulated (10 M) crystals fill this gap. Using a combination of transient grating spectroscopy and laser-baser resonant ultrasound spectroscopy, it is confirmed that there is a shear elastic instability in the lattice, being significantly stronger than in any other martensitic material and also than what the first-principles calculations for Ni-Mn-Ga predict. The experimental results reveal that the instability is directly related to the lattice modulations. A lattice-scale mechanism of dynamic faulting of the modulation sequence that explains this behavior is proposed; this mechanism can explain the extraordinary mobility of twin boundaries in 10 M., Comment: Manuscript accepted to Advanced Materials. Supplementary material (text and figures) is available as ancillary file

Machine Learning (ML) is a common tool to interpret and predict the behavior of distributed computing systems, e.g., to optimize the task distribution between devices. As more and more data is created by Internet of Things (IoT) devices, data processing and ML training are carried out by edge devices in close proximity. To ensure Quality of Service (QoS) throughout these operations, systems are supervised and dynamically adapted with the help of ML. However, as long as ML models are not retrained, they fail to capture gradual shifts in the variable distribution, leading to an inaccurate view of the system state. Moreover, as the prediction accuracy decreases, the reporting device should actively resolve uncertainties to improve the model's precision. Such a level of self-determination could be provided by Active Inference (ACI) -- a concept from neuroscience that describes how the brain constantly predicts and evaluates sensory information to decrease long-term surprise. We encompassed these concepts in a single action-perception cycle, which we implemented for distributed agents in a smart manufacturing use case. As a result, we showed how our ACI agent was able to quickly and traceably solve an optimization problem while fulfilling QoS requirements.

Compute Continuum (CC) systems comprise a vast number of devices distributed over computational tiers. Evaluating business requirements, i.e., Service Level Objectives (SLOs), requires collecting data from all those devices; if SLOs are violated, devices must be reconfigured to ensure correct operation. If done centrally, this dramatically increases the number of devices and variables that must be considered, while creating an enormous communication overhead. To address this, we (1) introduce a causality filter based on Markov blankets (MB) that limits the number of variables that each device must track, (2) evaluate SLOs decentralized on a device basis, and (3) infer optimal device configuration for fulfilling SLOs. We evaluated our methodology by analyzing video stream transformations and providing device configurations that ensure the Quality of Service (QoS). The devices thus perceived their environment and acted accordingly -- a form of decentralized intelligence.

Irreversible plastic forming of B19$^\prime$ martensite of the NiTi shape memory alloy is discussed within the framework of continuum mechanics. It is suggested that the main mechanism arises from coupling between martensite reorientation and coordinated $[100](001)_{\rm M}$ dislocation slip. A heuristic model is proposed, showing that the ${(20\bar{1})_{\rm M}}$ deformation-twin bands, commonly observed in experiments, can be interpreted as a combination of dislocation-mediated kink bands, appearing due to strong plastic anisotropy, and reversible twinning of martensite. We introduce a term 'kwinking' for this combination of reversible twinning and irreversible plastic kinking. The model is subsequently formulated using the tools of nonlinear elasticity theory of martensite and crystal plasticity, introducing 'kwink interfaces' as planar, kinematically compatible interfaces between two differently plastically slipped variants of martensite. It is shown that the ${(20\bar{1})_{\rm M}}$ kwink bands may be understood as resultsing from energy minimization, and that their nucleation and growth and their pairing with $(100)_{\rm M}$ twins into specific patterns enables low-energy plastic forming of NiTi martensite. We conclude that kwinking makes plastic deformation of B19$^\prime$ martensite in polycrystalline NiTi possible despite only one slip system being available., Comment: Manuscript accepted to International Journal of Plasticity

Presently, gamma-ray tracking in germanium segmented detectors is realised by applying two advanced, complex algorithms. While they have already triggered an intensive R&D, they are still subject to further improvements. Making such algorithms effective, online in real time conditions and/or offline for deeper analysis, in data pipelines do require many additional software developments. This review paper gives an overview of the various bricks of software produced so far by the AGATA collaboration. It provides hints of what is foreseen for the next phases of the project up to its full configuration namely with 180 capsules in the array.

Quantum instruments describe outcome probability as well as state change induced by measurement of a quantum system. Incompatibility of two instruments, i. e. the impossibility to realize them simultaneously on a given quantum system, generalizes incompatibility of channels and incompatibility of positive operator-valued measures (POVMs). We derive implications of instrument compatibility for the induced POVMs and channels. We also study relation of instrument compatibility to the concept of non-disturbance. Finally, we prove equivalence between instrument compatibility and postprocessing of certain instruments, which we term complementary instruments. We illustrate our findings on examples of various classes of instruments., Comment: accepted version

In field electron emission (FE) studies, to interpret current-voltage data and extract characterization parameters, we use smooth planar metal-like emitter (SPME) methodology and a data-analysis plot. Three types exist: Millikan-Lauritsen (ML), Fowler-Nordheim (FN) and Murphy-Good (MG) plots. In SPME methodology, ML and FN plots are slightly curved but a MG plot is nearly straight. 1956 MG FE theory is better physics than 1928 FN theory, so we expect MG plots to be more precise than ML or FN plots. Current-voltage data are often converted: measured voltage to (apparent) macroscopic field, current to macroscopic current density. Thus, four different data-input forms exist. Over-simplified models of system behaviour are widely assumed. Whether simple use of a data-analysis plot is a valid interpretation method is often neglected. Published FE studies seem to contain a high incidence of spurious values for "field enhancement factor". A procedure (the "Orthodoxy Test") described in 2013 allows a validity check: around 40 % of a small sample of results were spuriously high. To assist data interpretation and validity checks, a simple user-friendly webtool has been designed by the lead author. As inputs, this needs system specification data and "range-limits" data from any of the three plot forms, using any of the four data-input forms. The webtool then applies the Orthodoxy Test, and -- if passed -- extracts characterization parameters. This study reports: (1) systematic tests of webtool functionality, using simulated input data prepared using Extended MG FE theory; and (2) systematic comparisons of the three different data-plot types, to check how well extracted parameter values match simulation input values. A summary review of relevant theory is given. For formal emission areas, the MG plot performs better than FN and ML plots. This is important for FE science., Comment: 16 printed pages, 8 figures. Open-access published version

The Karlsruhe Tritium Neutrino (KATRIN) experiment is designed to measure a high-precision integral spectrum of the endpoint region of T2 beta decay, with the primary goal of probing the absolute mass scale of the neutrino. After a first tritium commissioning campaign in 2018, the experiment has been regularly running since 2019, and in its first two measurement campaigns has already achieved a sub-eV sensitivity. After 1000 days of data-taking, KATRIN's design sensitivity is 0.2 eV at the 90% confidence level. In this white paper we describe the current status of KATRIN; explore prospects for measuring the neutrino mass and other physics observables, including sterile neutrinos and other beyond-Standard-Model hypotheses; and discuss research-and-development projects that may further improve the KATRIN sensitivity., Comment: Contribution to Snowmass 2021. 70 pages excluding references; 35 figures. Author list updated June 2023

Studying sequential measurements is of the utmost importance to both the foundational aspects of quantum theory and the practical implementations of quantum technologies, with both of these applications being abstractly described by the concatenation of quantum instruments into a sequence of certain length. In general, the choice of instrument at any given step in the sequence can be conditionally chosen based on the classical results of all preceding instruments. For two instruments in a sequence we consider the conditional second instrument as an effective way of post-processing the first instrument into a new one. This is similar to how a measurement described by a positive operator-valued measure (POVM) can be post-processed into another by way of classical randomization of its outcomes using a stochastic matrix. In this work we study the post-processing relation of instruments and the partial order it induces on their equivalence classes. We characterize the greatest and the least element of this order, give examples of post-processings between different types of instruments and draw connections between post-processings of some of these instruments and their induced POVMs.

We address the question of existence of private quantum channel for qubits encoded in polarization degrees of freedom of a photon, that remains secure even if multi-photon (instead of single-photon) pulse is emitted. We show that random unitary channel distributed according to SU(2) Haar measure has this property. Further we analyze the qubit unitary k-designs. We show they ensure security if the photons' parity of the source is guaranteed. Otherwise, the qubit unitary k-designs do not guarantee perfect security., Comment: 8 pages

Probabilistic storage and retrieval (PSR) of unitary quantum dynamics is possible with exponentially small failure probability with respect to the number of systems used as a quantum memory [PRL 122, 170502 (2019)]. Here we study improvements due to a priori knowledge about the unitary transformation to be stored. In particular, we study $N \rightarrow 1$ PSR of qubit phase gates, i.e. qubit rotations a round $Z$ axis with an unknown angle, and show that if we access the gate only $N$-times, the optimal probability of perfect retrieving of its single use is $N/(N+1)$. We propose a quantum circuit realization for the optimal protocol and show that programmable phase gate [PRL 88, 047905 (2002)] can be turned into $(2^k-1)\rightarrow 1$ optimal PSR of phase gates and requires only $k$ CNOT gates, while having exponentially small failure probability in $k$., Comment: 9 pages, 7 figures

If two identical copies of a completely depolarizing channel are put into a superposition of their possible causal orders, they can transmit non-zero classical information. Here, we study how well we can transmit classical information with $N$ depolarizing channels put in superposition of $M$ causal orders via quantum SWITCH. We calculate Holevo quantity if the superposition uses only cyclic permutations of channels and find that it increases with $M$ and it is independent of $N$. For a qubit it never reaches $1$ if we are increasing $M$. On the other hand, the classical capacity decreases with the dimension $d$ of the message system. Further, for $N=3$ and $N=4$ we studied superposition of all causal orders and uniformly superposed causal orders belonging to different cosets created by cyclic permutation subgroup., Comment: 16pages, 8figures, and 2tables. Thoroughly revised with a major revision in Section.IV. A new Author has been added. Comments are welcome

The KATRIN (Karlsruhe Tritium Neutrino) experiment investigates the energetic endpoint of the tritium beta-decay spectrum to determine the effective mass of the electron anti-neutrino. The collaboration has reported a first mass measurement result at this TAUP-2019 conference. The TRISTAN project aims at detecting a keV-sterile neutrino signature by measuring the entire tritium beta-decay spectrum with an upgraded KATRIN system. One of the greatest challenges is to handle the high signal rates generated by the strong activity of the KATRIN tritium source while maintaining a good energy resolution. Therefore, a novel multi-pixel silicon drift detector and read-out system are being designed to handle rates of about 100 Mcps with an energy resolution better than 300 eV (FWHM). This report presents succinctly the KATRIN experiment, the TRISTAN project, then the results of the first 7-pixels prototype measurement campaign and finally describes the construction of the first TRISTAN module composed of 166 SDD-pixels as well as its implementation in KATRIN experiment.

In this report we present the status of the MAgnetized Disk and Mirror Axion eXperiment (MADMAX), the first dielectric haloscope for the direct search of dark matter axions in the mass range of 40 to 400 $\mu$eV. MADMAX will consist of several parallel dielectric disks, which are placed in a strong magnetic field and with adjustable separations. This setting is expected to allow for an observable emission of axion induced electromagnetic waves at a frequency between 10 and 100 GHz corresponding to the axion mass. The present document orignated from a status report to the DESY PRC in 2019.

The work presents a thermomechanical model for polycrystalline NiTi-based shape memory alloys developed within the framework of generalized standard solids, which is able to cover loading-mode dependent localization of the martensitic transformation. The key point is the introduction of a novel austenite-martensite interaction term responsible for strain-softening of the material. Mathematical properties of the model are analyzed and a suitable regularization and a time-discrete approximation for numerical implementation to the finite-element method are proposed. Model performance is illustrated on two numerical simulations: tension of a superelastic NiTi ribbon and bending of a superelastic NiTi tube.

Some beautiful identities involving hook contents of Young diagrams have been found in the field of quantum information processing, along with a combinatorial proof. We here give a representation theoretic proof of these identities and a number of generalizations. Our proof is based on trace identities for elements belonging to a class of permutation centralizer algebras. These algebras have been found to underlie the combinatorics of composite gauge invariant operators in quantum field theory, with applications in the AdS/CFT correspondence. Based on these algebras, we discuss some analogies between quantum information processing tasks and the combinatorics of composite quantum fields and argue that this can be fruitful interface between quantum information and quantum field theory, with implications for AdS/CFT., Comment: 11 pages plus 4-page Appendix. Version 2 - minor typo corrected

We address the question of a quantum memory storage of quantum dynamics. In particular, we design an optimal protocol for $N\to 1$ probabilistic storage-and-retrieval of unitary channels on $d$-dimensional quantum systems. If we may access the unknown unitary gate only $N$-times, the optimal success probability of perfect retrieval of its single use is $N/(N-1+d^2)$. The derived size of the memory system exponentially improves the known upper bound on the size of the program register needed for probabilistic programmable quantum processors. Our results are closely related to probabilistic perfect alignment of reference frames and probabilistic port-based teleportation., Comment: 5+8 pages, 4 figures

Based on the work of A. Vershik, we introduce two new combinatorial identities. We show how these identities can be used to prove a new hook-content identity. The main motivation for deriving this identity was a particular optimization problem in the field of quantum information processing., Comment: 10 pages, 1 figure