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Federica Bianco

Publications and source records attributed to Federica Bianco.

At least 19 recordsLinked to original sources

Coherent multi-dimensional widefield microscopy

Understanding how electronic excitations evolve across space and time is essential for revealing the microscopic processes underlying quantum and optoelectronic materials. However, existing approaches cannot simultaneously resolve ultrafast coherent dynamics with microscopic spatial information: pump-probe microscopy lacks access to quantum coherence, while two-dimensional electronic spectroscopy (2DES) requires slow point-by-point scanning for spatial resolution. Here we introduce a widefield two-dimensional electronic spectroscopy microscope (2DESM) combining multidimensional coherent spectroscopy with widefield imaging, enabling simultaneous femtosecond temporal and micrometer spatial resolution across a broadband spectral range. Applying 2DESM to hBN-encapsulated WSe2, we directly visualize spatial variations in exciton coherence and relaxation associated with the local environment, establishing 2DESM as a powerful platform for probing many-body interactions, energy transport, and structure-function relationships in low-dimensional materials and devices.

physics.optics

The Cross-Survey Decade: A Call to Action

By 2027, three flagship wide-field surveys will be operating simultaneously from ground and space, observing overlapping sky and representing more than $6 billion in US and European public investment. Together they will produce overlapping petabyte-scale datasets across thousands of square degrees. This is a different class of challenge: the observations are no longer the bottleneck; realizing their joint scientific return now depends on shared computational infrastructure and coordination. Decades of community studies show that combining these datasets does more than improve precision. For science ranging from weak lensing to transient discovery and Galactic-plane astronomy, joint processing and analysis can unlock capabilities no single survey provides alone. Yet the required infrastructure -- joint pixel-level processing, cross-calibration and validation, interoperable data access, and the people to build and sustain it -- falls outside any single mission or institution's mandate. We issue a call to action for cross-survey science infrastructure, built around four pillars: (1) joint pixel-level processing and validation; (2) an AI-ready data substrate for scientific foundation models; (3) standardized, interoperable data access across surveys, democratizing participation in astrophysical discovery; and (4) dedicated personnel and career pathways. We outline concrete steps for policymakers, agencies, observatories, universities, the research community, and philanthropy, and argue that the moment to act is now, while foundational technical choices can still be aligned at a fraction of the cost of reconciling them later.

astro-ph.IM

An Information-Theoretic Metric for Transient Classification and Novelty Detection

The development of the observing strategy for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) requires a broad optimization across science cases inside and outside of time-domain astronomy. We introduce a novel metric for transient science with LSST based on information-theoretic cross-entropy. We demonstrate its utility for distinguishing populations of objects and discuss applications for observing strategy / detection pipeline optimization as well as novelty detection and follow-up resource allocation.

astro-ph.IM

Distance estimate to NGC 6951 from supernova siblings Type IIP SN 2020dpw and Type Ib SN 2021sjt

{Supernova (SN) siblings are powerful tools used to calibrate and improve distance measurement methods, and to make the systematic uncertainty to distances to their host galaxies considerably lower compared to other techniques.} {In this paper we present distance estimates to NGC6951, a galaxy that hosted the Type IIP SN~2020dpw, the Type Ib SN~2021sjt, and three other SNe.} {Photometric observations of the two objects were carried out using two 80cm RC telescopes located in Hungary, while spectra were obtained from the LCO and the WiseRep database. For the distance estimates, we applied the expanding photosphere method (EPM), which connects the observed angular radius ($θ$) of a SN to its physical radius and is related to the velocity of the photosphere ($v_{\rm ph}$). Although the EPM is mostly applied to derive the distance of Type IIP SNe, in the literature there are several examples of this technique being used for Type IIn and stripped-envelope SNe as well. Therefore, we made another attempt to infer the distance of the Type Ib SN~2021sjt by applying the EPM together with its Type IIP sibling SN~2020dpw. } {Our analysis resulted in a distance of $25.76 \pm 0.34 (\rm random) \pm 5.51$ (systematic) Mpc and $24.57 \pm 1.27 (\rm random) \pm 4.64$ (systematic) Mpc for SN~2020dpw and SN~2021sjt, respectively. Systematic errors were estimated with respect to the used dilution factor, the interstellar reddening, and the date of the explosion (which was fixed to a value between the last non-detection and the first detection for each object).} {The obtained distance values agree with each other and with the literature, which shows the validity of the methods used. In this way, new and perhaps improved distance estimates to NGC 6951 were obtained, and the applicability of the EPM for Type Ib SNe was tested.}

astro-ph.HE

Active electron cooling of graphene

In the emergent field of quantum technology, the ability to manage heat at the nanoscale and in cryogenic conditions is crucial for enhancing device performance in terms of noise, coherence, and sensitivity. Here, we demonstrate the active cooling and refrigeration of the electron gas in a graphene thermal transistor, by taking advantage of nanoscale superconductive tunnel contacts able to pump or extract heat directly from the electrons in the device. Our prototypes achieved a top cooling of electrons in graphene of about 15 mK at a bath temperature of about 450 mK, demonstrating the viability of the proposed device architecture. Our experimental findings are backed by a detailed thermal model that accurately replicated the observed device behavior. Alternative cooling schemes and perspectives are discussed in light of the reported results. Finally, our graphene thermal transistor could find application in superconducting hybrid quantum technologies.

cond-mat.mes-hall

First Temperature Profile of a Stellar Flare using Differential Chromatic Refraction

We present the first derivation of a stellar flare temperature profile from single-band photometry. Stellar flare DWF030225.574-545707.45129 was detected in 2015 by the Dark Energy Camera as part of the Deeper, Wider, Faster Programme. The brightness ($Δm_g = -6.12$) of this flare, combined with the high air mass ($1.45 \lesssim X \lesssim 1.75$) and blue filter (DES $g$, 398-548 nm) in which it was observed, provided ideal conditions to measure the zenith-ward apparent motion of the source due to differential chromatic refraction (DCR) and, from that, infer the effective temperature of the event. We model the flare's spectral energy distribution as a blackbody to produce the constraints on flare temperature and geometric properties derived from single-band photometry. We additionally demonstrate how simplistic assumptions on the flaring spectrum, as well as on the evolution of flare geometry, can result in solutions that overestimate effective temperature. Exploiting DCR enables studying chromatic phenomena with ground-based astrophysical surveys and stellar flares on M-dwarfs are a particularly enticing target for such studies due to their ubiquity across the sky, and the heightened color contrast between their red quiescent photospheres and the blue flare emission. Our novel method will enable similar temperature constraints for large sample of objects in upcoming photometric surveys like the Vera C. Rubin Legacy Survey of Space and Time.

astro-ph.SR

Transformer-Based Neural Network for Transient Detection without Image Subtraction

We introduce a transformer-based neural network for the accurate classification of real and bogus transient detections in astronomical images. This network advances beyond the conventional convolutional neural network (CNN) methods, widely used in image processing tasks, by adopting an architecture better suited for detailed pixel-by-pixel comparison. The architecture enables efficient analysis of search and template images only, thus removing the necessity for computationally-expensive difference imaging, while maintaining high performance. Our primary evaluation was conducted using the autoScan dataset from the Dark Energy Survey (DES), where the network achieved a classification accuracy of 97.4% and diminishing performance utility for difference image as the size of the training set grew. Further experiments with DES data confirmed that the network can operate at a similar level even when the input images are not centered on the supernova candidate. These findings highlight the network's effectiveness in enhancing both accuracy and efficiency of supernova detection in large-scale astronomical surveys.

cs.CV

Multi-messenger Gravitational Lensing

We introduce the rapidly emerging field of multi-messenger gravitational lensing - the discovery and science of gravitationally lensed phenomena in the distant universe through the combination of multiple messengers. This is framed by gravitational lensing phenomenology that has grown since the first discoveries in the 20th century, messengers that span 30 orders of magnitude in energy from high energy neutrinos to gravitational waves, and powerful "survey facilities" that are capable of continually scanning the sky for transient and variable sources. Within this context, the main focus is on discoveries and science that are feasible in the next 5-10 years with current and imminent technology including the LIGO-Virgo-KAGRA network of gravitational wave detectors, the Vera C. Rubin Observatory, and contemporaneous gamma/X-ray satellites and radio surveys. The scientific impact of even one multi-messenger gravitational lensing discovery will be transformational and reach across fundamental physics, cosmology and astrophysics. We describe these scientific opportunities and the key challenges along the path to achieving them. This article is the introduction to the Theme Issue of the Philosophical Transactions of The Royal Society A on the topic of Multi-messenger Gravitational Lensing, and describes the consensus that emerged at the associated Theo Murphy Discussion Meeting in March 2024.

astro-ph.HE

Autoencoder Reconstruction of Cosmological Microlensing Magnification Maps

Enhanced modeling of microlensing variations in light curves of strongly lensed quasars improves measurements of cosmological time delays, the Hubble Constant, and quasar structure. Traditional methods for modeling extra-galactic microlensing rely on computationally expensive magnification map generation. With large datasets expected from wide-field surveys like the Vera C. Rubin Legacy Survey of Space and Time, including thousands of lensed quasars and hundreds of multiply imaged supernovae, faster approaches become essential. We introduce a deep-learning model that is trained on pre-computed magnification maps covering the parameter space on a grid of k, g, and s. Our autoencoder creates a low-dimensional latent space representation of these maps, enabling efficient map generation. Quantifying the performance of magnification map generation from a low dimensional space is an essential step in the roadmap to develop neural network-based models that can replace traditional feed-forward simulation at much lower computational costs. We develop metrics to study various aspects of the autoencoder generated maps and show that the reconstruction is reliable. Even though we observe a mild loss of resolution in the generated maps, we find this effect to be smaller than the smoothing effect of convolving the original map with a source of a plausible size for its accretion disk in the red end of the optical spectrum and larger wavelengths and particularly one suitable for studying the Broad-Line Region of quasars. Used to generate large samples of on-demand magnification maps, our model can enable fast modeling of microlensing variability in lensed quasars and supernovae.

astro-ph.IM

Tailoring coherent charge transport in graphene by deterministic defect generation

Harnessing the wave-nature of charge carriers in solid state devices, electron optics investigates and exploits coherent phenomena, in analogy with optics and photonics. Typically, this requires complex electronic devices leveraging macroscopically coherent charge transport in two-dimensional electron gases and superconductors. Here, collective coherent effects are induced in a simple counterintuitive architecture by defect engineering. Deterministically introduced lattice defects in graphene enable the phase coherent charge transport by playing the role of potential barriers, instead of scattering centres as conventionally considered. Thus, graphene preserves its quasi-ballistic quantum transport and can support phase-matched charge carrier waves. Based on this approach, multiple electronic Fabry-Pèrot cavities are formed by creating periodically alternating defective and pristine nano-stripes through low energy electron-beam irradiation. Indeed, defective stripes behave as partially reflecting mirrors and resonantly confine the charge carrier waves within the pristine areas, giving rise to Fabry-Pèrot resonant modes. These modes experimentally manifest as sheet resistance oscillations, as also confirmed by Landauer-Büttiker simulations. Moreover, these coherent phenomena survive up to 30 K for both polarities of charge carriers, contrarily to traditional monopolar electrostatically created Fabry-Pèrot interferometers. Our study positions defective graphene as an innovative platform for coherent electronic devices, with potential applications in nano and quantum technologies.

cond-mat.mes-hall

Rubin ToO 2024: Envisioning the Vera C. Rubin Observatory LSST Target of Opportunity program

The Legacy Survey of Space and Time (LSST) at Vera C. Rubin Observatory is planned to begin in the Fall of 2025. The LSST survey cadence has been designed via a community-driven process regulated by the Survey Cadence Optimization Committee (SCOC), which recommended up to 3% of the observing time to carry out Target of Opportunity (ToO) observations. Experts from the scientific community, Rubin Observatory personnel, and members of the SCOC were brought together to deliver a recommendation for the implementation of the ToO program during a workshop held in March 2024. Four main science cases were identified: gravitational wave multi-messenger astronomy, high energy neutrinos, Galactic supernovae, and small potentially hazardous asteroids possible impactors. Additional science cases were identified and briefly addressed in the documents, including lensed or poorly localized gamma-ray bursts and twilight discoveries. Trigger prioritization, automated response, and detailed strategies were discussed for each science case. This document represents the outcome of the Rubin ToO 2024 workshop, with additional contributions from members of the Rubin Science Collaborations. The implementation of the selection criteria and strategies presented in this document has been endorsed in the SCOC Phase 3 Recommendations document (PSTN-056). Although the ToO program is still to be finalized, this document serves as a baseline plan for ToO observations with the Rubin Observatory.

astro-ph.IM

Recovered SN Ia rate from simulated LSST images

The Legacy Survey of Space and Time (LSST) will revolutionize Time Domain Astronomy by detecting millions of transients. In particular, it is expected to increment the number of type Ia supernovae (SNIa) of a factor of 100 compared to existing samples up to z~1.2. Such a high number of events will dramatically reduce statistical uncertainties in the analysis of SNIa properties and rates. However, the impact of all other sources of uncertainty on the measurement must still be evaluated. The comprehension and reduction of such uncertainties will be fundamental both for cosmology and stellar evolution studies, as measuring the SNIa rate can put constraints on the evolutionary scenarios of different SNIa progenitors. We use simulated data from the DESC Data Challenge 2 (DC2) and LSST Data Preview 0 (DP0) to measure the SNIa rate on a 15 deg2 region of the Wide-Fast-Deep area. We select a sample of SN candidates detected on difference images, associate them to the host galaxy, and retrieve their photometric redshifts (z-phot). Then, we test different light curves classification methods, with and without redshift priors. We discuss how the distribution in redshift measured for the SN candidates changes according to the selected host galaxy and redshift estimate. We measure the SNIa rate analyzing the impact of uncertainties due to z-phot, host galaxy association and classification on the distribution in redshift of the starting sample. We found a 17% average lost fraction of SNIa with respect to the simulated sample. As 10% of the bias is due to the uncertainty on the z-phot alone (which also affects classification when used as a prior), it results to be the major source of uncertainty. We discuss possible reduction of the errors in the measurement of the SNIa rate, including synergies with other surveys, which may help using the rate to discriminate different progenitor models.

astro-ph.CO

Latest Developments and Opportunities in Sky Survey

Policy Brief on "Latest Developments and Opportunities in Sky Survey", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. Sky surveys have been a crucial tool in advancing our understanding of the Universe. The last few decades have seen an explosion in the number and scope of sky surveys, both ground-based and space-based. This growth has led to a wealth of data that has enabled us to make significant advances in many areas of astronomy, and help understand the physics of the universe. They have helped us discover new astronomical objects, the origin of the elements, dark matter and dark energy, the accelerated expansion of the universe, and gravitational waves. They have helped us study the distribution of neutral and ionized matter in the Universe and test our theories about the origin and evolution of galaxies, stars, and planets. We explore recent advances and potential avenues in sky surveys, and examine how these developments may impact the field of international astronomical research. The policy webinar took place during the G20 presidency in India (2023). A summary based on the seven panels can be found here: arxiv:2401.04623.

astro-ph.IM

Every Datapoint Counts: Stellar Flares as a Case Study of Atmosphere Aided Studies of Transients in the LSST Era

Due to their short timescale, stellar flares are a challenging target for the most modern synoptic sky surveys. The upcoming Vera C. Rubin Legacy Survey of Space and Time (LSST), a project designed to collect more data than any precursor survey, is unlikely to detect flares with more than one data point in its main survey. We developed a methodology to enable LSST studies of stellar flares, with a focus on flare temperature and temperature evolution, which remain poorly constrained compared to flare morphology. By leveraging the sensitivity expected from the Rubin system, Differential Chromatic Refraction can be used to constrain flare temperature from a single-epoch detection, which will enable statistical studies of flare temperatures and constrain models of the physical processes behind flare emission using the unprecedentedly high volume of data produced by Rubin over the 10-year LSST. We model the refraction effect as a function of the atmospheric column density, photometric filter, and temperature of the flare, and show that flare temperatures at or above ~4,000K can be constrained by a single g-band observation at airmass X > 1.2, given the minimum specified requirement on single-visit relative astrometric accuracy of LSST, and that a surprisingly large number of LSST observations is in fact likely be conducted at X > 1.2, in spite of image quality requirements pushing the survey to preferentially low X. Having failed to measure flare DCR in LSST precursor surveys, we make recommendations on survey design and data products that enable these studies in LSST and other future surveys.

astro-ph.IM

AstroInformatics: Recommendations for Global Cooperation

Policy Brief on "AstroInformatics, Recommendations for Global Collaboration", distilled from panel discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. The deliberations encompassed a wide array of topics, including broad astroinformatics, sky surveys, large-scale international initiatives, global data repositories, space-related data, regional and international collaborative efforts, as well as workforce development within the field. These discussions comprehensively addressed the current status, notable achievements, and the manifold challenges that the field of astroinformatics currently confronts. The G20 nations present a unique opportunity due to their abundant human and technological capabilities, coupled with their widespread geographical representation. Leveraging these strengths, significant strides can be made in various domains. These include, but are not limited to, the advancement of STEM education and workforce development, the promotion of equitable resource utilization, and contributions to fields such as Earth Science and Climate Science. We present a concise overview, followed by specific recommendations that pertain to both ground-based and space data initiatives. Our team remains readily available to furnish further elaboration on any of these proposals as required. Furthermore, we anticipate further engagement during the upcoming G20 presidencies in Brazil (2024) and South Africa (2025) to ensure the continued discussion and realization of these objectives. The policy webinar took place during the G20 presidency in India (2023). Notes based on the seven panels will be separately published.

astro-ph.IM

Anti-Black racism workshop during the Vera C. Rubin Observatory virtual 2021 Project and Community Workshop

Systemic racism is a ubiquitous theme in societies worldwide and plays a central role in shaping our economic, social, and academic institutions. The Vera C. Rubin Observatory is a major US ground-based facility based in Chile with international participation. The Observatory is an example of excellence and will deliver the largest survey of the sky ever attempted. Rubin's full scientific and social potential can not be attained without addressing systemic racism and associated barriers to equity, diversity, and inclusion (EDI). During Rubin's 2021 virtual Project and Community Workshop (PCW), the annual Rubin community-based meeting, an anti-Black racism workshop took place, facilitated by 'The BIPOC Project' organization. About 60 members from different parts of the Rubin ecosystem participated. We describe the motivation, organization, challenges, outcomes, and near- and long-term goals of this workshop.

physics.soc-ph

What's the Difference? The potential for Convolutional Neural Networks for transient detection without template subtraction

We present a study of the potential for Convolutional Neural Networks (CNNs) to enable separation of astrophysical transients from image artifacts, a task known as "real-bogus" classification without requiring a template subtracted (or difference) image which requires a computationally expensive process to generate, involving image matching on small spatial scales in large volumes of data. Using data from the Dark Energy Survey, we explore the use of CNNs to (1) automate the "real-bogus" classification, (2) reduce the computational costs of transient discovery. We compare the efficiency of two CNNs with similar architectures, one that uses "image triplets" (templates, search, and difference image) and one that takes as input the template and search only. We measure the decrease in efficiency associated with the loss of information in input finding that the testing accuracy is reduced from 96% to 91.1%. We further investigate how the latter model learns the required information from the template and search by exploring the saliency maps. Our work (1) confirms that CNNs are excellent models for "real-bogus" classification that rely exclusively on the imaging data and require no feature engineering task; (2) demonstrates that high-accuracy (> 90%) models can be built without the need to construct difference images, but some accuracy is lost. Since once trained, neural networks can generate predictions at minimal computational costs, we argue that future implementations of this methodology could dramatically reduce the computational costs in the detection of transients in synoptic surveys like Rubin Observatory's Legacy Survey of Space and Time by bypassing the Difference Image Analysis entirely.

cs.CV

Operability timescale of defect-engineered graphene

Defects in the lattice are of primal importance to tune graphene chemical, thermal and electronic properties. Electron-beam irradiation is an easy method to induce defects in graphene following pre-designed patterns, but no systematic study of the time evolution of the resulting defects is available. In this paper, the change over time of defected sites created in graphene with low-energy ($\leq 20$ keV) electron irradiation is studied both experimentally via micro-Raman spectroscopy for a period of $6\times 10^3$ hours and through molecular dynamics simulations. During the first 10 h, the structural defects are stable at the highest density value. Subsequently, the crystal partially reconstructs, eventually reaching a stable, less defected condition after more than one month. The simulations allow the rationalization of the processes at the atomic level and confirm that the irradiation induces composite clusters of defects of different nature rather than well-defined nanoholes as in the case of high-energy electrons. The presented results identify the timescale of the defects stability, thus establishing the operability timespan of engineerable defect-rich graphene devices with applications in nanoelectronics. Moreover, long-lasting chemical reactivity of the defective graphene is pointed out. This property can be exploited to functionalize graphene for sensing and energy storage applications.

cond-mat.mtrl-sci