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Context. Blazar AO 0235+164, located at redshift z = 0.94, has undergone several sharp multi-spectral-range flaring episodes during the last decades. In particular, the episodes peaking in 2008 and 2015, that received extensive multi-wavelength coverage, exhibited interesting behavior. Aims. We study the actual origin of these two observed flares by constraining the properties of the observed photo-polarimetric variability, those of the broad-band spectral energy-distribution and the observed time-evolution behavior of the source as seen by ultra-high resolution total-flux and polarimetric Very-long-baseline interferometry (VLBI) imaging. Methods. The analysis of VLBI images allows us to constrain kinematic and geometrical parameters of the 7 mm jet. We use the Discrete Correlation Function to compute the statistical correlation and the delays between emission at different spectral ranges. Multi-epoch modeling of the spectral energy distributions allows us to propose specific models of emission; in particular for the unusual spectral features observed in this source in the X-ray region of the spectrum during strong multi spectral-range flares. Results. We find that these X-ray spectral features can be explained by an emission component originating in a separate particle distribution than the one responsible for the two standard blazar bumps. This is in agreement with the results of our correlation analysis that do not find a strong correlation between the X-rays and the remaining spectral ranges. We find that both external Compton dominated and synchrotron self-Compton dominated models can explain the observed spectral energy distributions. However, synchrotron self-Compton models are strongly favored by the delays and geometrical parameters inferred from the observations.

Optimizing the energy efficiency of driving processes provides valuable insights into the underlying physics and is of crucial importance for numerous applications, from biological processes to the design of machines and robots. Knowledge of optimal driving protocols is particularly valuable at the microscale, where energy supply is often limited. Here we investigate experimentally and theoretically the paradigmatic optimization problem of moving a potential carrying a load through a fluid, in a finite time and over a given distance, in such a way that the required work is minimal. An important step towards more realistic systems is the consideration of memory effects in the surrounding fluid, which are ubiquitous in real-world applications. Therefore, our experiments were performed in viscous and viscoelastic media, which are typical environments for synthetic and biological processes on the microscale. Despite marked differences between the protocols in both fluids, we find that the optimal control protocol and the corresponding average particle trajectory always obey a time-reversal symmetry. We show that this symmetry, which surprisingly applies here to a class of processes far from thermal equilibrium, holds universally for various systems, including active, granular, and long-range correlated media in their linear regimes. The uncovered symmetry provides a rigorous and versatile criterion for optimal control that greatly facilitates the search for energy-efficient transport strategies in a wide range of systems. Using a machine learning algorithm, we demonstrate that the algorithmic exploitation of time-reversal symmetry can significantly enhance the performance of numerical optimization algorithms., Comment: 16 pages with 10 figures, accepted for publication in PRX

Structured illumination can reject out-of-focus signal from a sample, enabling high-speed and high-contrast imaging over large areas with widefield detection optics. Currently, this optical-sectioning technique is limited by image reconstruction artefacts and the need for sequential imaging of multiple colour channels. We combine multicolour interferometric pattern generation with machine-learning processing, permitting high-contrast, real-time reconstruction of image data. The method is insensitive to background noise and unevenly phase-stepped illumination patterns. We validate the method in silico and demonstrate its application on diverse specimens, ranging from fixed and live biological cells to synthetic biosystems, imaging at up to 37 Hz across a 44 x 44 $\mu m^2$ field of view.

The analysis of configurable systems, i.e., systems those behaviors depend on parameters or support various features, is challenging due to the exponential blowup arising in the number of configuration options. This volume contains the post-proceedings of TiCSA 2023, the first workshop on Trends in Configurable Systems Analysis, where current challenges and solutions in configurable systems analysis were presented and discussed.

We investigate the structural and dynamic properties of active Brownian particles (APs) confined within a soft annulus-shaped channel. Depending on the strength of the confinement and the P\'eclet number, we observe a novel re-entrant behavior that is not present in unconfined systems. Our findings are substantiated by numerical simulations and analytical considerations, revealing that this behavior arises from the strong coupling between the P\'eclet number and the effective confining dimensionality of the APs. Beyond highlighting the important influence of soft boundaries on APs, our research holds significance for future applications of micro-robotic systems.

We present the generation of transient polarization gratings at the nanoscale, achieved using a tailored accelerator configuration of the FERMI free electron laser. We demonstrate the capabilities of such a transient polarization grating by comparing its induced dynamics with the ones triggered by a more conventional intensity grating on a thin film ferrimagnetic alloy. While the signal of the intensity grating is dominated by the thermoelastic response of the system, such a contribution is suppressed in the case of the polarization grating. This exposes helicity-dependent magnetization dynamics that have so-far remained hidden under the large thermally driven response. We anticipate nanoscale transient polarization gratings to become useful for the study of any physical, chemical and biological systems possessing chiral symmetry.

We present the multiwavelength flaring activity of the blazar AO 0235+164 during its recent active period from 2013 to 2019. From a discrete correlation function (DCF) analysis, we find a significant (>95%) correlation between radio and $\gamma$-ray light curves with flares at longer wavelengths following flares at shorter wavelengths. We identify a new jet component in 43 GHz VLBA data that was ejected from the radio core on MJD $57246^{+26}_{-30}$ (2015 August 12), during the peak of the 2015 radio flare. From the analysis of the jet component, we derived a Doppler factor of $\delta_{\rm var}=28.5\pm8.4$, a bulk Lorentz factor of $\Gamma=16.8^{+3.6}_{-3.1}$, and an intrinsic viewing angle of $\theta_{\rm v}=1.42^{+1.07}_{-0.52}\textrm{ degrees}$. Investigation of the quasi-simultaneous radio data revealed a partially absorbed spectrum with the turnover frequency varying in the range of $10-70$ GHz and the peak flux density varying in the range of $0.7-4$ Jy. We find the synchrotron self-absorption magnetic field strength to be $B_{\rm SSA}=15.3^{+12.6}_{-14.0}$ mG at the peak of the 2015 radio flare, which is comparable to the equipartition magnetic field strength of $B_{\rm EQ}=43.6^{+10.6}_{-10.4}$ mG calculated for the same epoch. Additional analysis of the radio emission region in the relativistic jet of AO 0235+164 suggests that it did not significantly deviate from equipartition during its recent flaring activity., Comment: 13 pages, 11 figures, 4 tables; Accepted for publication in MNRAS

The sequence $(\operatorname{Ass}(R/I^n))_{n\in\mathbb{N}}$ of associated primes of powers of a monomial ideal $I$ in a polynomial ring $R$ eventually stabilizes by a known result by Markus Brodmann. L\^e Tu\^an Hoa gives an upper bound for the index where the stabilization occurs. This bound depends on the generators of the ideal and is obtained by separately bounding the powers of $I$ after which said sequence is non-decreasing and non-increasing, respectively. In this paper, we focus on the latter and call the smallest such number the copersistence index. We take up the proof idea of L\^e Tu\^an Hoa, who exploits a certain system of inequalities whose solution sets store information about the associated primes of powers of $I$. However, these proofs are entangled with a specific choice for the system of inequalities. In contrast to that, we present a generic ansatz to obtain an upper bound for the copersistence index that is uncoupled from this choice of the system. We establish properties for a system of inequalities to be eligible for this approach to work. We construct two suitable inequality systems to demonstrate how this ansatz yields upper bounds for the copersistence index and compare them with Hoa's.

Heterostructures of two-dimensional transition metal dichalcogenides (TMDs) are emerging as a promising platform for investigating exotic correlated states of matter. Here, we propose to engineer Bose-Fermi mixtures in these systems by coupling inter-layer excitons to doped charges in a trilayer structure. Their interactions are determined by the inter-layer trion, whose spin-selective nature allows excitons to mediate an attractive interaction between charge carriers of only one spin species. Remarkably, we find that this causes the system to become unstable to topological p+ip superconductivity at low temperatures. We then demonstrate a general mechanism to develop and control this unconventional state by tuning the trion binding energy using a solid-state Feshbach resonance., Comment: 11 pages, 5 figures. Final version

Feshbach resonances play a vital role in the success of cold atoms investigating strongly-correlated physics. The recent observation of their solid-state analog in the scattering of holes and intralayer excitons in transition metal dichalcogenides [Schwartz et al., Science 374, 336 (2021)] holds compelling promise for bringing fully controllable interactions to the field of semiconductors. Here, we demonstrate how tunneling-induced layer hybridization can lead to the emergence of two distinct classes of Feshbach resonances in atomically thin semiconductors. Based on microscopic scattering theory we show that these two types of Feshbach resonances allow to tune interactions between electrons and both short-lived intralayer, as well as long-lived interlayer excitons. We predict the exciton-electron scattering phase shift from first principles and show that the exciton-electron coupling is fully tunable from strong to vanishing interactions. The tunability of interactions opens the avenue to explore Bose-Fermi mixtures in solid-state systems in regimes that were previously only accessible in cold atom experiments., Comment: 6+3 pages, 4+1 figures

Applying a Weyl-Stratonovich transform to the evolution equation of the Wigner function in an electromagnetic field yields a multidimensional gauge-invariant equation which is numerically very challenging to solve. In this work, we apply simplifying assumptions for linear electromagnetic fields and the evolution of an electron in a plane (two-dimensional transport), which reduces the complexity and enables to gain first experiences with a gauge-invariant Wigner equation. We present an equation analysis and show that a finite difference approach for solving the high-order derivatives allows for reformulation into a Fredholm integral equation. The resolvent expansion of the latter contains consecutive integrals, which is favorable for Monte Carlo solution approaches. To that end, we present two stochastic (Monte Carlo) algorithms that evaluate averages of generic physical quantities or directly the Wigner function. The algorithms give rise to a quantum particle model, which interprets quantum transport in heuristic terms.

Fingerprints have long been recognized as a unique and reliable means of personal identification. Central to the analysis and enhancement of fingerprints is the concept of the fingerprint core. Although the location of the core is used in many applications, to the best of our knowledge, this study is the first to investigate the empirical distribution of the core over a large, combined dataset of rolled, as well as plain fingerprint recordings. We identify and investigate the extent of incomplete rolling during the rolled fingerprint acquisition and investigate the centrality of the core. After correcting for the incomplete rolling, we find that the core deviates from the fingerprint center by 5.7% $\pm$ 5.2% to 7.6% $\pm$ 6.9%, depending on the finger. Additionally, we find that the assumption of normal distribution of the core position of plain fingerprint recordings cannot be rejected, but for rolled ones it can. Therefore, we use a multi-step process to find the distribution of the rolled fingerprint recordings. The process consists of an Anderson-Darling normality test, the Bayesian Information Criterion to reduce the number of possible candidate distributions and finally a Generalized Monte Carlo goodness-of-fit procedure to find the best fitting distribution. We find the non-central Fischer distribution best describes the cores' horizontal positions. Finally, we investigate the correlation between mean core position offset and the NFIQ 2 score and find that the NFIQ 2 prefers rolled fingerprint recordings where the core sits slightly below the fingerprint center.

The extend of tool wear significantly affects blanking processes and has a decisive impact on product quality and productivity. For this reason, numerous scientists have addressed their research to wear monitoring systems in order to identify or even predict critical wear at an early stage. Existing approaches are mainly based on indirect monitoring using time series, which are used to detect critical wear states via thresholds or machine learning models. Nevertheless, differentiation between types of wear phenomena affecting the tool during blanking as well as quantification of worn surfaces is still limited in practice. While time series data provides partial insights into wear occurrence and evolution, direct monitoring techniques utilizing image data offer a more comprehensive perspective and increased robustness when dealing with varying process parameters. However, acquiring and processing this data in real-time is challenging. In particular, high dynamics combined with increasing strokes rates as well as the high dimensionality of image data have so far prevented the development of direct image-based monitoring systems. For this reason, this paper demonstrates how high-resolution images of tools at 600 spm can be captured and subsequently processed using semantic segmentation deep learning algorithms, more precisely Fully Convolutional Networks (FCN). 125,000 images of the tool are taken from successive strokes, and microscope images are captured to investigate the worn surfaces. Based on findings from the microscope images, selected images are labeled pixel by pixel according to their wear condition and used to train a FCN (U-Net).

Continual learning is a desirable feature in many modern machine learning applications, which allows in-field adaptation and updating, ranging from accommodating distribution shift, to fine-tuning, and to learning new tasks. For applications with privacy and low latency requirements, the compute and memory demands imposed by continual learning can be cost-prohibitive for resource-constraint edge platforms. Reducing computational precision through fully quantized training (FQT) simultaneously reduces memory footprint and increases compute efficiency for both training and inference. However, aggressive quantization especially integer FQT typically degrades model accuracy to unacceptable levels. In this paper, we propose a technique that leverages inexpensive Hadamard transforms to enable low-precision training with only integer matrix multiplications. We further determine which tensors need stochastic rounding and propose tiled matrix multiplication to enable low-bit width accumulators. We demonstrate the effectiveness of our technique on several human activity recognition datasets and CIFAR100 in a class incremental learning setting. We achieve less than 0.5% and 3% accuracy degradation while we quantize all matrix multiplications inputs down to 4-bits with 8-bit accumulators.

We show how the relatively initial or relatively terminal fixed points for a well-behaved functor $F$ form a pair of adjoint functors between $F$-coalgebras and $F$-algebras. We use the language of locally presentable categories to find sufficient conditions for existence of this adjunction. We show that relative fixed points may be characterized as (co)equalizers of the free (co)monad on $F$. In particular, when $F$ is a polynomial functor on $\mathsf{Set}$ the relative fixed points are a quotient or subset of the free term algebra or the cofree term coalgebra. We give examples of the relative fixed points for polynomial functors and an example which is the Sierpinski carpet. Lastly, we prove a general preservation result for relative fixed points., Comment: 26 pages

The COVID-19 pandemic led to unprecedented levels of federal aid transfers to state governments. Did this funding increase benefit state incumbents electorally? Identifying the effect of revenue windfalls on economic voting is challenging because whatever conditions led to the influx of cash might also benefit or harm incumbent politicians for a variety of other reasons. We develop an instrument that allows us to predict allocations to states based on variation in congressional representation. We find that incumbents in state-wide races in 2020, 2021, and 2022 performed significantly better in states that received more relief funding due to their over-representation in Congress. These results are robust across specifications and after adjusting for a variety of economic and political controls. We consistently find that the pandemic-period electoral advantage of incumbent politicians in states receiving more aid substantially exceeds the more modest advantage these politicians enjoyed during pre-pandemic elections. This paper contributes to our understanding of economic voting and the incumbency advantage during times of crisis as well as the downstream electoral consequences of both the COVID-19 pandemic and of unequal political representation at the federal level., 1 Introduction In response to the COVID-19 pandemic, the U.S. federal government transferred nearly $1 trillion in aid to state and local governments--the largest influx of federal money in response [...]