arXiv subjects

Alessandro Sciarra

Publications and source records attributed to Alessandro Sciarra.

At least 19 recordsLinked to original sources

arXiv2026

On credit attribution and research software: A case study from lattice QCD

Questions of authorship, credit attribution, and the recognition of research software contributions have become increasingly prominent in those constantly growing research areas for which software constitutes an essential part of the research process. While general guidelines and best practices exist, their application in concrete situations often raises nontrivial interpretative and procedural issues. This article presents a documented case study from lattice QCD research, illustrating how the development of numerical strategies, long-term software infrastructure, and conceptual extensions of existing work can give rise to complex questions of authorship, priority, and credit attribution. Rather than discussing the underlying scientific results, the focus is on the sequence of events, the role of software as a long-term research infrastructure, and the interaction with established mechanisms for credit attribution and research integrity assessment. The aim of this work is to contribute to transparency and discussion on how current practices and guidelines are applied in realistic collaborative environments, and to highlight structural tensions that may arise between open scientific collaboration, software sustainability, and traditional notions of authorship. The article is intended as a factual account and reflection on research practice, and aims to stimulate discussion on whether additional community standards for recognising long-term research software contributions may be beneficial within lattice QCD.

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arXiv2026

SMILE-UHURA Challenge -- Small Vessel Segmentation at Mesoscopic Scale from Ultra-High Resolution 7T Magnetic Resonance Angiograms

The human brain receives nutrients and oxygen through an intricate network of blood vessels. Pathology affecting small vessels, at the mesoscopic scale, represents a critical vulnerability within the cerebral blood supply and can lead to severe conditions, such as Cerebral Small Vessel Diseases. The advent of 7 Tesla MRI systems has enabled the acquisition of higher spatial resolution images, making it possible to visualise such vessels in the brain. However, the lack of publicly available annotated datasets has impeded the development of robust, machine learning-driven segmentation algorithms. To address this, the SMILE-UHURA challenge was organised. This challenge, held in conjunction with the ISBI 2023, in Cartagena de Indias, Colombia, aimed to provide a platform for researchers working on related topics. The SMILE-UHURA challenge addresses the gap in publicly available annotated datasets by providing an annotated dataset of Time-of-Flight angiography acquired with 7T MRI. This dataset was created through a combination of automated pre-segmentation and extensive manual refinement. In this manuscript, sixteen submitted methods and two baseline methods are compared both quantitatively and qualitatively on two different datasets: held-out test MRAs from the same dataset as the training data (with labels kept secret) and a separate 7T ToF MRA dataset where both input volumes and labels are kept secret. The results demonstrate that most of the submitted deep learning methods, trained on the provided training dataset, achieved reliable segmentation performance. Dice scores reached up to 0.838 $\pm$ 0.066 and 0.716 $\pm$ 0.125 on the respective datasets, with an average performance of up to 0.804 $\pm$ 0.15.

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arXiv2026

Exact center symmetry and first-order phase transition in QCD with three degenerate dynamical quarks

We study QCD with three degenerate flavors of dynamical quarks using first-principles lattice simulations. For a specific choice of imaginary isospin chemical potential, this theory possesses an exact center symmetry, just like pure gauge theory. This exact symmetry is expected to be intact at low temperatures and spontaneously broken in the high-temperature regime. By analyzing the finite-size scaling of the Polyakov loop distribution, obtained with a dedicated multi-histogram approach, we demonstrate that there is a first-order deconfinement phase transition in between. Our results are obtained employing stout-smeared rooted staggered quarks at one lattice spacing. Using simulations at different quark masses we sketch the behavior of QCD in the mass-isospin chemical potential plane, shedding new light on this corner of the fundamental phase diagram of the strong interactions and the relationship between chiral symmetry breaking and deconfinement.

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arXiv2025

The chiral phase transition in the 3D Columbia plot

The nature of the chiral phase transition of QCD continues to represent a fundamental open problem in the study of strongly interacting matter. In recent years, significant progress has been achieved by exploiting systematic variations of theory parameters in regimes free of the sign problem. In this work, the idea of a follow-up investigation that extends a previous study at zero chemical potential is presented. A concrete programme for such an extension is discussed, outlining the required numerical steps, from data production to final analysis, and pointing to all the software tools that have been released to support these studies.

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arXiv2025

PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation

In the domain of medical imaging, many supervised learning based methods for segmentation face several challenges such as high variability in annotations from multiple experts, paucity of labelled data and class imbalanced datasets. These issues may result in segmentations that lack the requisite precision for clinical analysis and can be misleadingly overconfident without associated uncertainty quantification. This work proposes the PULASki method as a computationally efficient generative tool for biomedical image segmentation that accurately captures variability in expert annotations, even in small datasets. This approach makes use of an improved loss function based on statistical distances in a conditional variational autoencoder structure (Probabilistic UNet), which improves learning of the conditional decoder compared to the standard cross-entropy particularly in class imbalanced problems. The proposed method was analysed for two structurally different segmentation tasks (intracranial vessel and multiple sclerosis (MS) lesion) and compare our results to four well-established baselines in terms of quantitative metrics and qualitative output. These experiments involve class-imbalanced datasets characterised by challenging features, including suboptimal signal-to-noise ratios and high ambiguity. Empirical results demonstrate the PULASKi method outperforms all baselines at the 5\% significance level. Our experiments are also of the first to present a comparative study of the computationally feasible segmentation of complex geometries using 3D patches and the traditional use of 2D slices. The generated segmentations are shown to be much more anatomically plausible than in the 2D case, particularly for the vessel task.

cs.CV↗

arXiv2025

First-order phase transition in dynamical 3-flavor QCD at imaginary isospin

We revisit QCD with three mass-degenerate quark flavors at an imaginary isospin chemical potential set to 4 pi T/3. This choice corresponds to a special point in the parameter space, where the theory possesses an exact Z(3) center symmetry. Through a finite-size scaling analysis, we demonstrate that in this case the finite temperature QCD transition is of first order and entails singular behavior both in the Polyakov loop and in the quark condensate. Our results are based on simulations with stout-smeared staggered quarks and a dedicated multi-histogram analysis.

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arXiv2023

Automated SSIM Regression for Detection and Quantification of Motion Artefacts in Brain MR Images

Motion artefacts in magnetic resonance brain images can have a strong impact on diagnostic confidence. The assessment of MR image quality is fundamental before proceeding with the clinical diagnosis. Motion artefacts can alter the delineation of structures such as the brain, lesions or tumours and may require a repeat scan. Otherwise, an inaccurate (e.g. correct pathology but wrong severity) or incorrect diagnosis (e.g. wrong pathology) may occur. "\textit{Image quality assessment}" as a fast, automated step right after scanning can assist in deciding if the acquired images are diagnostically sufficient. An automated image quality assessment based on the structural similarity index (SSIM) regression through a residual neural network is proposed in this work. Additionally, a classification into different groups - by subdividing with SSIM ranges - is evaluated. Importantly, this method predicts SSIM values of an input image in the absence of a reference ground truth image. The networks were able to detect motion artefacts, and the best performance for the regression and classification task has always been achieved with ResNet-18 with contrast augmentation. The mean and standard deviation of residuals' distribution were $μ=-0.0009$ and $σ=0.0139$, respectively. Whilst for the classification task in 3, 5 and 10 classes, the best accuracies were 97, 95 and 89\%, respectively. The results show that the proposed method could be a tool for supporting neuro-radiologists and radiographers in evaluating image quality quickly.

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arXiv2022

StRegA: Unsupervised Anomaly Detection in Brain MRIs using a Compact Context-encoding Variational Autoencoder

Expert interpretation of anatomical images of the human brain is the central part of neuro-radiology. Several machine learning-based techniques have been proposed to assist in the analysis process. However, the ML models typically need to be trained to perform a specific task, e.g., brain tumour segmentation or classification. Not only do the corresponding training data require laborious manual annotations, but a wide variety of abnormalities can be present in a human brain MRI - even more than one simultaneously, which renders representation of all possible anomalies very challenging. Hence, a possible solution is an unsupervised anomaly detection (UAD) system that can learn a data distribution from an unlabelled dataset of healthy subjects and then be applied to detect out of distribution samples. Such a technique can then be used to detect anomalies - lesions or abnormalities, for example, brain tumours, without explicitly training the model for that specific pathology. Several Variational Autoencoder (VAE) based techniques have been proposed in the past for this task. Even though they perform very well on controlled artificially simulated anomalies, many of them perform poorly while detecting anomalies in clinical data. This research proposes a compact version of the "context-encoding" VAE (ceVAE) model, combined with pre and post-processing steps, creating a UAD pipeline (StRegA), which is more robust on clinical data, and shows its applicability in detecting anomalies such as tumours in brain MRIs. The proposed pipeline achieved a Dice score of 0.642$\pm$0.101 while detecting tumours in T2w images of the BraTS dataset and 0.859$\pm$0.112 while detecting artificially induced anomalies, while the best performing baseline achieved 0.522$\pm$0.135 and 0.783$\pm$0.111, respectively.

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arXiv2021

The QCD chiral phase transition for different numbers of quark flavours

We present results from a comprehensive study of the location of the chiral critical surface, which separates regions of first-order chiral transitions from analytic crossovers, in the bare parameter space of lattice QCD with unimproved staggered fermions. We study the theories with $N_f\in[2,8]$ and trace the chiral critical surface along diminishing lattice spacing, with $N_τ=\{4,6,8\}$. This allows for an extrapolation to the lattice chiral limit, where the surface has to terminate in a tricritical line, employing known tricritical scaling relations. Knowing the phase structure in the lattice bare parameter space allows to draw conclusions for the approach to the continuum and chiral limits taken in the appropriate order. Our data provide evidence for the continuum chiral limit to feature a second-order transition for all $N_f\in[2,7]$. We perform an analogous scaling analysis with already published data from $N_f=3$ $O(a)$-improved Wilson fermions, which is also consistent with a second-order transition in the continuum. A modified Columbia plot reflecting those results is suggested.

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arXiv2021

The chiral phase transition from strong to weak coupling

The order of the chiral phase transition of lattice QCD with unimproved staggered fermions is known to depend on the number of quark flavours, their masses and the lattice spacing. Previous studies in the literature for $N_f \in \{ 3,4 \}$ show first-order transitions, which weaken with decreasing lattice spacing. Here we investigate what happens when lattices are made coarser to establish contact to the strong coupling region. For $N_f \in \{4,8 \}$ we find a drastic weakening of the transition when going from $N_τ=4$ to $N_τ=2$, which is consistent with a second-order chiral transition reported in the literature for $N_f=4$ in the strong coupling limit. This implies a non-monotonic behaviour of the critical quark or pseudo-scalar meson mass, which separates first-order transitions from crossover behaviour, as a function of lattice spacing.

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arXiv2021

The QCD Deconfinement Critical Point for $N_\text{f}=2$ Flavors of Staggered Fermions

Quenched QCD at zero baryonic chemical potential undergoes a first-order deconfinement phase transition at a critical temperature $T_c$, which is related to the spontaneous breaking of the global center symmetry. Including heavy, dynamical quarks breaks the center symmetry explicitly and weakens the first-order phase transition. For decreasing quark masses the first-order phase transition turns into a smooth crossover at a $Z_2$-critical point. The critical quark mass corresponding to this point has been examined with $N_\text{f} = 2$ Wilson fermions for several $N_τ$ in a recent study within our group. For comparison, we also locate the critical point with $N_\text{f} = 2$ staggered fermions on $N_τ= 8$ lattices. For this purpose we perform Monte Carlo simulations for several quark mass values and various aspect ratios in order to extrapolate to the thermodynamic limit. The critical mass is obtained by fitting to a finite size scaling formula of the kurtosis of the Polyakov loop. Our results indicate large discretization effects, requiring simulations on lattices with $N_τ> 8$.

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arXiv2021

On the order of the QCD chiral phase transition for different numbers of quark flavours

The nature of the QCD chiral phase transition in the limit of vanishing quark masses has remained elusive for a long time, since it cannot be simulated directly on the lattice and is strongly cutoff-dependent. We report on a comprehensive ongoing study using unimproved staggered fermions with $N_\text{f}\in[2,8]$ mass-degenerate flavours on $N_τ\in\{4,6,8\}$ lattices, in which we locate the chiral critical surface separating regions with first-order transitions from crossover regions in the bare parameter space of the lattice theory. Employing the fact that it terminates in a tricritical line, this surface can be extrapolated to the chiral limit using tricritical scaling with known exponents. Knowing the order of the transitions in the lattice parameter space, conclusions for approaching the continuum chiral limit in the proper order can be drawn. While a narrow first-order region cannot be ruled out, we find initial evidence consistent with a second-order chiral transition in all massless theories with $N_\text{f}\leq 6$, and possibly up to the onset of the conformal window at $9\lesssim N_\text{f}^*\lesssim 12$. A reanalysis of already published $\mathcal{O}(a)$-improved $N_\text{f}=3$ Wilson data on $N_τ\in[4,12]$ is also consistent with tricritical scaling, and the associated change from first to second-order on the way to the continuum chiral limit. We discuss a modified Columbia plot and a phase diagram for many-flavour QCD that reflect these possible features.

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arXiv2021

ShuffleUNet: Super resolution of diffusion-weighted MRIs using deep learning

Diffusion-weighted magnetic resonance imaging (DW-MRI) can be used to characterise the microstructure of the nervous tissue, e.g. to delineate brain white matter connections in a non-invasive manner via fibre tracking. Magnetic Resonance Imaging (MRI) in high spatial resolution would play an important role in visualising such fibre tracts in a superior manner. However, obtaining an image of such resolution comes at the expense of longer scan time. Longer scan time can be associated with the increase of motion artefacts, due to the patient's psychological and physical conditions. Single Image Super-Resolution (SISR), a technique aimed to obtain high-resolution (HR) details from one single low-resolution (LR) input image, achieved with Deep Learning, is the focus of this study. Compared to interpolation techniques or sparse-coding algorithms, deep learning extracts prior knowledge from big datasets and produces superior MRI images from the low-resolution counterparts. In this research, a deep learning based super-resolution technique is proposed and has been applied for DW-MRI. Images from the IXI dataset have been used as the ground-truth and were artificially downsampled to simulate the low-resolution images. The proposed method has shown statistically significant improvement over the baselines and achieved an SSIM of $0.913\pm0.045$.

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arXiv2021

Deconfinement critical point of lattice QCD with $N_{\rm f}=2$ Wilson fermions

The ${\rm SU}(3)$ pure gauge theory exhibits a first-order thermal deconfinement transition due to spontaneous breaking of its global $Z_3$ center symmetry. When heavy dynamical quarks are added, this symmetry is broken explicitly and the transition weakens with decreasing quark mass until it disappears at a critical point. We compute the critical hopping parameter and the associated pion mass for lattice QCD with $N_f=2$ degenerate standard Wilson fermions on $N_τ\in\{6,8,10\}$ lattices, corresponding to lattice spacings $a=0.12\, {\rm fm}$, $a=0.09\, {\rm fm}$, $a=0.07\, {\rm fm}$, respectively. Significant cut-off effects are observed, with the first-order region growing as the lattice gets finer. While current lattices are still too coarse for a continuum extrapolation, we estimate $m_π^c\approx 4 {\rm GeV}$ with a remaining systematic error of $\sim 20\%$. Our results allow to assess the accuracy of the LO and NLO hopping expanded fermion determinant used in the literature for various purposes. We also provide a detailed investigation of the statistics required for this type of calculation, which is useful for similar investigations of the chiral transition.

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arXiv2020

Retrospective Motion Correction of MR Images using Prior-Assisted Deep Learning

In MRI, motion artefacts are among the most common types of artefacts. They can degrade images and render them unusable for accurate diagnosis. Traditional methods, such as prospective or retrospective motion correction, have been proposed to avoid or alleviate motion artefacts. Recently, several other methods based on deep learning approaches have been proposed to solve this problem. This work proposes to enhance the performance of existing deep learning models by the inclusion of additional information present as image priors. The proposed approach has shown promising results and will be further investigated for clinical validity.

eess.IV↗

arXiv2020

Finite size and cut-off effects on the Roberge-Weiss transition in $N_\text{f}=2$ QCD with Staggered fermions

In the absence of a genuine solution to the sign problem, lattice studies at imaginary quark chemical potential are an important tool to constrain the QCD phase diagram. We calculate the values of the tricritical quark masses in the Roberge-Weiss plane, $μ=\imathπT/3$, which separate mass regions with chiral and deconfinement phase transitions from the intermediate region, for QCD with $N_\text{f}=2$ unimproved staggered quarks on $N_τ=6$ lattices. A quantitative measure for the quality of finite size scaling plots is developed, which significantly reduces the subjective judgement required for fitting. We observe that larger aspect ratios are necessary to unambiguously determine the order of the transition than at $μ=0$. Comparing with previous results from $N_τ=4$ we find a $\sim50$% reduction in the light tricritical pion mass. The heavy tricritical pion mass stays roughly the same, but is too heavy to be resolved on $N_τ=6$ lattices and thus equally afflicted with cut-off effects. Further comparison with other discretizations suggests that current cut-off effects on the light critical masses are likely to be larger than $\sim100$%, implying a drastic shrinking of the chiral first-order region to possibly zero.

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arXiv2018

The QCD chiral phase transition from non-integer numbers of flavors

Attempts to extract the order of the chiral transition of QCD at zero chemical potential, with two dynamical flavors of massless quarks, from simulations with progressively decreasing pion mass have remained inconclusive because of their increasing numerical cost. In an alternative approach to this problem, we consider the path integral as a function of continuous number $N_\text{f}$ of degenerate quarks. If the transition in the chiral limit is first-order for $N_\text{f} \ge 3$, a second-order transition for $N_\text{f}=2$ then requires a tricritical point in between. This in turn implies tricritical scaling of the critical boundary line between the first-order and crossover regions as the chiral limit is approached. Non-integer numbers of fermion flavors are easily implemented within the staggered fermion discretization. Exploratory simulations at $μ=0$ and $N_\text{f} = 2.8, 2.6, 2.4, 2.2, 2.1$, on coarse $N_τ= 4$ lattices, indeed show a smooth variation of the critical mass mapping out a critical line in the $(m,N_\text{f})$-plane. For the smallest masses the line appears consistent with tricritical scaling, allowing for an extrapolation to the chiral limit.

hep-lat↗

arXiv2018

Progress on the nature of the QCD thermal transition as a function of quark flavors and masses

We investigate to which extent we can exploit the dependence of the order of the chiral transition on the number of light degenerate flavors $N_\text{f}$, re-interpreted as continuous parameter in the path integral formulation, as a means to perform a controlled chiral extrapolation and deduce the order of the transition for the case $N_\text{f}=2$, which is still under debate.

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