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HERMES-Pathfinder is a space-borne mission based on a constellation of six nano-satellites flying in a low-Earth orbit. The 3U CubeSats, to be launched in early 2025, host miniaturized instruments with a hybrid Silicon Drift Detector/scintillator photodetector system, sensitive to both X-rays and gamma-rays. A seventh payload unit is installed onboard SpIRIT, an Australian-Italian nano-satellite developed by a consortium led by the University of Melbourne and launched in December 2023. The project aims at demonstrating the feasibility of Gamma-Ray Burst detection and localization using miniaturized instruments onboard nano-satellites. The HERMES flight model payloads were exposed to multiple well-known radioactive sources for spectroscopic calibration under controlled laboratory conditions. The analysis of the calibration data allows both to determine the detector parameters, necessary to map instrumental units to accurate energy measurements, and to assess the performance of the instruments. We report on these efforts and quantify features such as spectroscopic resolution and energy thresholds, at different temperatures and for all payloads of the constellation. Finally we review the performance of the HERMES payload as a photon counter, and discuss the strengths and the limitations of the architecture.

HERMES (High Energy Rapid Modular Ensemble of Satellites) Pathfinder mission aims to observe and localize Gamma Ray Bursts (GRBs) and other transients using a constellation of nanosatellites in low-Earth orbit (LEO). Scheduled for launch in early 2025, the 3U CubeSats will host miniaturized instruments featuring a hybrid Silicon Drift Detector (SDD) and GAGG:Ce scintillator photodetector system, sensitive to X-rays and gamma-rays across a wide energy range. Each HERMES payload contains 120 SDD cells, each with a sensitive area of 45 mm^2, organized into 12 matrices, reading out 60 12.1x6.94x15.0 mm^3 GAGG:Ce scintillators. Photons interacting with an SDD are identified as X-ray events (2-60 keV), while photons in the 20-2000 keV range absorbed by the crystals produce scintillation light, which is read by two SDDs, allowing event discrimination. The detector system, including front-end and back-end electronics, a power supply unit, a chip-scale atomic clock, and a payload data handling unit, fits within a 10x10x10 cm^3 volume, weighs 1.5 kg, and has a maximum power consumption of about 2 W. This paper outlines the development of the HERMES constellation, the design and selection of the payload detectors, and laboratory testing, presenting the results of detector calibrations and environmental tests to provide a comprehensive status update of the mission., Comment: 8 pages, 6 figures. Proceedings of SPIE 13093, Space Telescopes and Instrumentation 2024: Ultraviolet to Gamma Ray

The dynamical mechanical analysis of blood generally uses models inspired by conventional flows, assuming scale-independent homogeneous flows and without considering fluid-surface boundary interactions. The present experimental study highlights the relevance of using an approach in line with physiological reality providing a strong interaction between the fluid and the boundary interface. New dynamic properties of human blood plasma are found: a finite shear elastic response (solid-like property) is identified in nearly static conditions, which also depends on the scale (being reinforced at small scales). The elastic behavior is confirmed by the induction of local hot and cold thermodynamic states evidencing a thermo-mechanical coupling in blood plasma so far known only in elastic materials. This finding opens new routes for medical diagnosis and device fabrication.

We examine the influence at room temperature of the deposit of a water layer on the phonon dynamics of a solid. It is shown that the water wetting at the surface of an Alumina monocrystal has deep effects on acoustic phonons, propagating over several hundred microns distance and taking place on a relatively long time scale. The effect of the wetting at the boundary is two-fold: a hardening of both transverse and longitudinal acoustic phonons is observed as well as a relaxation of internal stresses. These acoustic phonon energy changes were observed by inelastic X-ray scattering up to 40 meV energy loss, allowing us to probe the solid at different depths from the surface.

HERMES (High Energy Rapid Modular Ensemble of Satellites) Pathfinder is a space-borne mission based on a constellation of six nano-satellites flying in a low-Earth orbit (LEO). The 3U CubeSats, to be launched in early 2025, host miniaturized instruments with a hybrid Silicon Drift Detector/GAGG:Ce scintillator photodetector system, sensitive to X-rays and gamma-rays in a large energy band. HERMES will operate in conjunction with Australian Space Industry Responsive Intelligent Thermal (SpIRIT) 6U CubeSat, launched in December 2023. HERMES will probe the temporal emission of bright high-energy transients such as Gamma-Ray Bursts (GRBs), ensuring a fast transient localization in a field of view of several steradians exploiting the triangulation technique. HERMES intrinsically modular transient monitoring experiment represents a keystone capability to complement the next generation of gravitational wave experiments. In this paper we outline the scientific case, development and programmatic status of the mission, Comment: 13 pages, 16 figures. Proceedings of SPIE "Astronomical Telescopes and Instrumentation" 2024. arXiv admin note: text overlap with arXiv:2210.13866

Quantum Computing (QC) offers significant potential to enhance scientific discovery in fields such as quantum chemistry, optimization, and artificial intelligence. Yet QC faces challenges due to the noisy intermediate-scale quantum era's inherent external noise issues. This paper discusses the integration of QC as a computational accelerator within classical scientific high-performance computing (HPC) systems. By leveraging a broad spectrum of simulators and hardware technologies, we propose a hardware-agnostic framework for augmenting classical HPC with QC capabilities. Drawing on the HPC expertise of the Oak Ridge National Laboratory (ORNL) and the HPC lifecycle management of the Department of Energy (DOE), our approach focuses on the strategic incorporation of QC capabilities and acceleration into existing scientific HPC workflows. This includes detailed analyses, benchmarks, and code optimization driven by the needs of the DOE and ORNL missions. Our comprehensive framework integrates hardware, software, workflows, and user interfaces to foster a synergistic environment for quantum and classical computing research. This paper outlines plans to unlock new computational possibilities, driving forward scientific inquiry and innovation in a wide array of research domains.

The microscopic understanding of the dramatic increase in viscosity of liquids when cooled towards the glass transition is a major unresolved issue in condensed matter physics. Here, we use machine learning methods to accelerate molecular dynamics simulations with first-principles accuracy for the glass-former toluene. We show that the increase in viscosity is intimately linked to the increasing number of dynamically correlated molecules $N^*$. While certain hallmark features of glassy dynamics, like physical aging, are linked to $N^*$ as well, others, like relaxation stretching, are not.

Semiconducting alloys, in particular SiGe, have been employed for several decades as high-temperature thermoelectric materials. Devising strategies to reduce their thermal conductivity may provide a substantial improvement in their thermoelectric performance also at lower temperatures. We have carried out an ab initio investigation of the thermal conductivity of SiGe alloys with random and spatially correlated mass disorder employing the Quasi-Harmonic Green-Kubo (QHGK) theory with force constants computed by density functional theory. Leveraging QHGK and the hydrodynamic extrapolation to achieve size convergence, we obtained a detailed understanding of lattice heat conduction in SiGe and demonstrated that colored disorder suppresses thermal transport across the acoustic vibrational spectrum, leading to up to a 4-fold enhancement in the intrinsic thermoelectric figure of merit.

The Space Industry Responsive Intelligent Thermal (SpIRIT) 6U CubeSat is a mission led by The University of Melbourne in cooperation with the Italian Space Agency. Launched in a 510 km Polar Sun Synchronous Orbit in December 2023, SpIRIT carries multiple subsystems for scientific and technology demonstration. The main payload is the HERMES instrument for detection of high-energy astrophysics transients (Gamma Ray Bursts), and for studies of their variability at scales below 1 ms. The satellite includes a novel thermal management system for its class, based on a Stirling-cycle cooler and deployable thermal radiator, designed to cool HERMES to reduce instrumental background noise. A low-latency communication subsystem based on a sat-phone network is supporting rapid transmission of time-critical data and telecommands. SpIRIT is also equipped with a set of RGB and thermal IR cameras, connected to an on-board image processing unit with artificial intelligence capabilities for autonomous feature recognition. To effectively manage all interfaces between different subsystems and mission stakeholders, the University of Melbourne developed an instrument control unit (PMS) which operates all payloads. PMS also provides backup uninterruptible power to the HERMES instrument through a supercapacitor-based UPS for safe instrument shutdown in case of platform power interruptions. This paper first presents a mission and payload overview, and early in-orbit results, along with lessons learned throughout the mission. This work not only sheds light on the novelty of some of the on-board technologies onboard and on their potential impact to enable greater utilization of CubeSats for scientific missions, but also offers insights into the practical challenges and accomplishments related to developing and operating a multi-organization CubeSat with a complex array of instruments and systems., Comment: 12 pages, 38th Annual Small Satellite Conference

Gamma Ray Bursts (GRBs) bridge relativistic astrophysics and multi-messenger astronomy. Space-based gamma/X-ray wide field detectors have proven essential to detect and localize the highly variable GRB prompt emission, which is also a counterpart of gravitational wave events. We study the capabilities to detect long and short GRBs by the High Energy Rapid Modular Ensemble of Satellites (HERMES) Pathfinder (HP) and SpIRIT, namely a swarm of six 3U CubeSats to be launched in early 2025, and a 6U CubeSat launched on December 1st 2023. We also study the capabilities of two advanced configurations of swarms of >8 satellites with improved detector performances (HERMES Constellations). The HERMES detectors, sensitive down to ~2-3 keV, will be able to detect faint/soft GRBs which comprise X-ray flashes and high redshift bursts. By combining state-of-the-art long and short GRB population models with a description of the single module performance, we estimate that HP will detect ~195^{+22}_{-21} long GRBs (3.4^{+0.3}_{-0.8} at redshift z>6) and ~19^{+5}_{-3} short GRBs per year. The larger HERMES Constellations under study can detect between ~1300 and ~3000 long GRBs per year and between ~160 and ~400 short GRBs per year, depending on the chosen configuration, with a rate of long GRBs above z>6 between 30 and 75 per year. Finally, we explore the capabilities of HERMES to detect short GRBs as electromagnetic counterparts of binary neutron star (BNS) mergers detected as gravitational signals by current and future ground-based interferometers. Under the assumption that the GRB jets are structured, we estimate that HP can provide up to 1 (14) yr^{-1} joint detections during the fifth LIGO-Virgo-KAGRA observing run (Einstein Telescope single triangle 10 km arm configuration). These numbers become 4 (100) yr^{-1}, respectively, for the HERMES Constellation configuration., Comment: 13 pages, 6 figures, 4 tabels. Accepted for publication by Astronomy & Astrophysics

A language model (LM) is a mapping from a linguistic context to an output token. However, much remains to be known about this mapping, including how its geometric properties relate to its function. We take a high-level geometric approach to its analysis, observing, across five pre-trained transformer-based LMs and three input datasets, a distinct phase characterized by high intrinsic dimensionality. During this phase, representations (1) correspond to the first full linguistic abstraction of the input; (2) are the first to viably transfer to downstream tasks; (3) predict each other across different LMs. Moreover, we find that an earlier onset of the phase strongly predicts better language modelling performance. In short, our results suggest that a central high-dimensionality phase underlies core linguistic processing in many common LM architectures.

The increasing prevalence of Large Language Models (LMs) in critical applications highlights the need for controlled language generation strategies that are not only computationally efficient but that also enjoy performance guarantees. To achieve this, we use a common model of concept semantics as linearly represented in an LM's latent space. In particular, we take the view that natural language generation traces a trajectory in this continuous semantic space, realized by the language model's hidden activations. This view permits a control-theoretic treatment of text generation in latent space, in which we propose a lightweight, gradient-free intervention that dynamically steers trajectories away from regions corresponding to undesired meanings. Crucially, we show that this intervention, which we compute in closed form, is guaranteed (in probability) to steer the output into the allowed region. Finally, we demonstrate on a toxicity avoidance objective that the intervention steers language away from undesired content while maintaining text quality.

After decades of improvements in cooling techniques of several atomic species and in finding methods for the achievement of stable quantum mixtures, the field is now ready for an extensive use of such a versatile experimental platform for the investigation of a variety of physical problems. Among them, relevant examples are the dynamics of impurities in a quantum gas, the miscibility condition of different gases, the study of exotic topological structures, the interplay between magnetism and superfluidity, the formation of artificial molecules, or new few-body states. We illustrate the differences among possible quantum mixtures, be they homonuclear spin mixtures or heteronuclear ones, and show how they can be exploited to investigate a plethora of topics from the few-body to the many-body regime. In particular, we discuss quantum mixtures of ultracold gases under three different perspectives: systems made of a few atoms of different kinds, single impurities immersed in a host quantum gas, and quantum mixtures of two interacting gases. We restrict the discussion to single harmonic or flat traps, predominantly in a three-dimensional configuration. A selection of results on recent experiments and possible interesting future directions are given., Comment: 36 pages, 7 figures

The minimization of the magnetic field plays a crucial role in ultracold gas research. For instance, the contact interaction dominates all the other energy scales in the zero magnetic field limit, giving rise to novel quantum phases of matter. However, lowering magnetic fields well below the mG level is often challenging in ultracold gas experiments. In this article, we apply Landau-Zener spectroscopy to characterize and reduce the magnetic field on an ultracold gas of sodium atoms to a few tens of {\mu}G. The lowest magnetic field achieved here opens to observing novel phases of matter with ultracold spinor Bose gases., Comment: 9 pages, 7 figures

Transport theory describes the response of a macroscopic current to a thermodynamic force, thus producing entropy and apparently violating time-reversal symmetry. In this note I report a pedagogical derivation of the Green-Kubo formula for transport coefficients that highlights the intrinsically dynamical nature of this formula and showcases the relation between the apparent breach of time-reversal symmetry and the non-commutativity of the low-frequency / low-wavevector limits of the conserved-density susceptibilities, from which the formula can be established.

Over the last decade, an increasing body of evidence has emerged, supporting the existence of a metastable liquid-liquid critical point in supercooled water, whereby two distinct liquid phases of different densities coexist. Analysing long molecular dynamics simulations performed using deep neural-network force fields trained to accurate quantum mechanical data, we demonstrate that the low-density liquid phase displays a strong propensity toward spontaneous polarization, as witnessed by large and long-lived collective dipole fluctuations. Our findings suggest that the dynamical stability of the low-density phase, and hence the transition from high-density to low-density liquid, is triggered by a collective process involving an accumulation of rotational angular jumps, which could ignite large dipole fluctuations. This dynamical transition involves subtle changes in the electronic polarizability of water molecules which affects their rotational mobility within the two phases. These findings hold the potential for catalyzing new activity in the search for dielectric-based probes of the putative second critical point.

This paper presents a systematic literature review in Computer Science that provide an overview of the initiatives related to digital misinformation. This is an exploratory study that covers research from 1993 to 2020, focusing on the investigation of the phenomenon of misinformation. The review consists of 788 studies from SCOPUS, IEEE, and ACM digital libraries, synthesizing the primary research directions and sociotechnical challenges. These challenges are classified into Physical, Empirical, Syntactic, Semantic, Pragmatic, and Social dimensions, drawing from Organizational Semiotics. The mapping identifies issues related to the concept of misinformation, highlights deficiencies in mitigation strategies, discusses challenges in approaching stakeholders, and unveils various sociotechnical aspects relevant to understanding and mitigating the harmful effects of digital misinformation. As contributions, this study present a novel categorization of mitigation strategies, a sociotechnical taxonomy for classifying types of false information and elaborate on the inter-relation of sociotechnical aspects and their impacts., Comment: This study is part of the main author's PhD, focusing on digital misinformation's sociotechnical aspects. It contributes to understanding and combating misinformation. The full thesis is available at: https://acervodigital.ufpr.br/xmlui/handle/1884/85764, providing further insight into the methodological rigor, theoretical underpinnings, and highlighting the need for multidisciplinary approaches

Description of quantum many-body dynamics is extremely challenging on classical computers, as it can involve many degrees of freedom. On the other hand, the time evolution of quantum states is a natural application for quantum computers, which are designed to efficiently perform unitary transformations. In this paper we study quantum algorithms for response functions, relevant for describing different reactions governed by linear response. We consider a qubit-efficient mapping on a lattice, which can be efficiently performed using momentum-space basis states. We analyze the advantages and disadvantages of this approach, focusing on the nuclear two-body system and a typical response function relevant for electron scattering as an example. We investigate ground-state preparation, controlled time evolution and the required measurements. We examine circuit depth and the hardware noise level required to interpret the signal.

Nonlocal games play a crucial role in quantum information theory and have numerous applications in certification and cryptographic protocols. Kalai et al. (STOC 2023) introduced a procedure to compile a nonlocal game into a single-prover interactive proof, using a quantum homomorphic encryption scheme, and showed that their compilation method preserves the classical bound of the game. Natarajan and Zhang (FOCS 2023) then showed that the quantum bound is preserved for the specific case of the CHSH game. Extending the proof techniques of Natarajan and Zhang, we show that the compilation procedure of Kalai et al. preserves the quantum bound for two classes of games: XOR games and d-outcome CHSH games. We also establish that, for any pair of qubit measurements, there exists an XOR game such that its optimal winning probability serves as a self-test for that particular pair of measurements., Comment: 22 pages, new result added and corrected typos

Transformer-based language models (LMs) track contextual information through large, hard-coded input windows. We introduce MemoryPrompt, a leaner approach in which the LM is complemented by a small auxiliary recurrent network that passes information to the LM by prefixing its regular input with a sequence of vectors, akin to soft prompts, without requiring LM finetuning. Tested on a task designed to probe a LM's ability to keep track of multiple fact updates, a MemoryPrompt-augmented LM outperforms much larger LMs that have access to the full input history. We also test MemoryPrompt on a long-distance dialogue dataset, where its performance is comparable to that of a model conditioned on the entire conversation history. In both experiments we also observe that, unlike full-finetuning approaches, MemoryPrompt does not suffer from catastrophic forgetting when adapted to new tasks, thus not disrupting the generalist capabilities of the underlying LM., Comment: Published as conference paper at LREC-COLING 2024

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the probability distribution of the off-diagonal elements of a Wishart matrix, we develop a consistent and unbiased estimator for the Seebeck coefficient whose statistical uncertainty can be arbitrarily reduced in the long-time limit. To validate the effectiveness of our method, we benchmark it against extensive equilibrium molecular dynamics simulations conducted on molten $\mathrm{CsF}$ using empirical force fields. We then employ this procedure to calculate the Seebeck coefficient of molten $\mathrm{NaCl}$, $\mathrm{KCl}$ and $\mathrm{LiCl}$ using neural-network force fields trained on ab initio data over a range of pressure-temperature conditions., Comment: 9 pages, 4 figures

The HERMES Technologic and Scientific Pathfinder project is a constellation of six CubeSats aiming to observe transient high-energy events such as the Gamma Ray Bursts (GRBs). HERMES will be the first space telescope to include a siswich detector, able to perform spectroscopy in the 2 keV to 2 MeV energy band. The particular siswich architecture, which combines a solid-state Silicon Drift Detector and a scintillator crystal, requires specific calibration procedures that have not been yet standardized in a pipeline. We present in this paper the HERMES calibration pipeline, mescal, intended for raw HERMES data energy calibration and formatting. The software is designed to deal with the particularities of the siswich architecture and to minimize user interaction, including also an automated calibration line identification procedure, and an independent calibration of each detector pixel, in its two different operating modes. The mescal pipeline can set the basis for similar applications in future siswich telescopes.

We describe an algorithm which, given two essential curves on a surface $S$, computes their distance in the curve graph of $S$, up to multiplicative and additive errors. As an application, we present an algorithm to decide the Nielsen-Thurston type (periodic, reducible, or pseudo-Anosov) of a mapping class of $S$. The novelty of our algorithms lies in the fact that their running time is polynomial in the size of the input and in the complexity of $S$ -- say, its Euler characteristic. This is in contrast with previously known algorithms, which run in polynomial time in the size of the input for any fixed surface $S$., Comment: 47 pages, 21 figures

The topic of the present lecture notes are two-species quantum mixtures composed of a deeply degenerate Fermi gas and a second component, the latter being fermionic or bosonic. A key ingredient is the possibility to tune the $s$-wave interaction between the different species by means of magnetically controlled Feshbach resonances, which allow us to investigate regimes of strong interactions. In two case studies, we review our experiments on mixtures of $^6$Li fermions with fermionic $^{40}$K or bosonic $^{41}$K atoms and on mixtures of fermionic $^{161}$Dy with $^{40}$K atoms. We cover various topics of fermionic quantum many-body physics, ranging from impurity physics and quasiparticles over phase separation to the formation of ultracold molecules and progress towards novel superfluids., Comment: Proceedings of the International Summer School "Enrico Ferm'', Course CCXI, Quantum Mixtures with Ultra-cold Atoms, Varenna, Lago di Como, 18-23 July 2022

Numerical simulation is an important method for verifying the quantum circuits used to simulate low-energy nuclear states. However, real-world applications of quantum computing for nuclear theory often generate deep quantum circuits that place demanding memory and processing requirements on conventional simulation methods. Here, we present advances in high-performance numerical simulations of deep quantum circuits to efficiently verify the accuracy of low-energy nuclear physics applications. Our approach employs several novel methods for accelerating the numerical simulation including 1- and 2-qubit gate fusion techniques as well as management of simulated mid-circuit measurements to verify state preparation circuits. We test these methods across a variety of high-performance computing systems and our results show that circuits up to 21 qubits and more than 115,000,000 gates can be efficiently simulated.

Language model prompt optimization research has shown that semantically and grammatically well-formed manually crafted prompts are routinely outperformed by automatically generated token sequences with no apparent meaning or syntactic structure, including sequences of vectors from a model's embedding space. We use machine-generated prompts to probe how models respond to input that is not composed of natural language expressions. We study the behavior of models of different sizes in multiple semantic tasks in response to both continuous and discrete machine-generated prompts, and compare it to the behavior in response to human-generated natural-language prompts. Even when producing a similar output, machine-generated and human prompts trigger different response patterns through the network processing pathways, including different perplexities, different attention and output entropy distributions, and different unit activation profiles. We provide preliminary insight into the nature of the units activated by different prompt types, suggesting that only natural language prompts recruit a genuinely linguistic circuit., Comment: Findings of EMNLP 2023 Camera-Ready

For a language model (LM) to faithfully model human language, it must compress vast, potentially infinite information into relatively few dimensions. We propose analyzing compression in (pre-trained) LMs from two points of view: geometric and information-theoretic. We demonstrate that the two views are highly correlated, such that the intrinsic geometric dimension of linguistic data predicts their coding length under the LM. We then show that, in turn, high compression of a linguistic dataset predicts rapid adaptation to that dataset, confirming that being able to compress linguistic information is an important part of successful LM performance. As a practical byproduct of our analysis, we evaluate a battery of intrinsic dimension estimators for the first time on linguistic data, showing that only some encapsulate the relationship between information-theoretic compression, geometric compression, and ease-of-adaptation., Comment: EMNLP 2023 Camera-Ready

We describe an algorithm to decide whether two genus-two surfaces embedded in the 3-sphere are isotopic or not. The algorithm employs well-known techniques in 3-manifolds topology, as well as a new algorithmic solution to a problem on free groups., Comment: 65 pages, 22 figures

The occurrence of a noncollinear magnetic structure at a Mn monolayer grown epitaxially on Fe(100) is predicted theoretically, using spinor density-functional theory, and observed experimentally, using x-ray magnetic circular dichroism (XMCD) and linear dichroism (XMLD) spectroscopies. The combined use of XMCD and XMLD at the Mn-absorption edge allows us to assess the existence of ferromagnetic and antiferromagnetic order at the interface, and also to determine the moment orientations with element specificity. The experimental results thus obtained are in excellent agreement with the magnetic structure determined theoretically.

The time-honored Allen-Feldman theory of heat transport in glasses is generally assumed to predict a finite value for the thermal conductivity, even if it neglects the anharmonic broadening of vibrational normal modes. We demonstrate that the harmonic approximation predicts that the bulk lattice thermal conductivity of harmonic solids inevitably diverges at any temperature, irrespective of configurational disorder, and that its ability to represent the heat-transport properties observed experimentally in most glasses is implicitly due to finite-size effects. Our theoretical analysis is thoroughly benchmarked against careful numerical simulations. Our findings thus reveal that a proper account of anharmonic effects is indispensable to predict a finite value for the bulk thermal conductivity in any solid material, be it crystalline or glassy., Comment: 11 pages, 6 figures

We present a method, based on the classical Green-Kubo theory of linear response, to compute the heat conductivity of extended systems, leveraging energy-density, rather than energy-current, fluctuations, thus avoiding the need to devise an analytical expression for the macroscopic energy flux. The implementation of this method requires the evaluation of the long-wavelength and low-frequency limits of a suitably defined correlation function, which we perform using a combination of recently-introduced cepstral-analysis and Bayesian extrapolation techniques. Our methodology is demonstrated against standard current-based Green-Kubo results for liquid argon and water, and compared with a recently proposed similar technique, which utilizes mass-density, instead of energy-density, fluctuations., Comment: 8 pages, 5 figures

The dynamics of (few) electrons dissolved in an ionic fluid--as when a small amount of metal is added to a solution while upholding its electronic insulation--manifests interesting properties that can be ascribed to nontrivial topological features of particle transport (e.g., Thouless' pumps). In the adiabatic regime, the charge distribution and the dynamics of these dissolved electrons are uniquely determined by the nuclear configuration. Yet, their localization into effective potential wells and their diffusivity are dictated by how the self-interaction is modeled. In this article, we investigate the role of self-interaction in the description of localization and transport properties of dissolved electrons in non-stoichiometric molten salts. Although the account for the exact (Fock) exchange strongly localizes the dissolved electrons, decreasing their tunneling probability and diffusivity, we show that the dynamics of the ions and of the dissolved electrons are largely uncorrelated, irrespective of the degree to which the electron self-interaction is treated, and in accordance with topological arguments., Comment: Accepted version. 7 pages, 6 figures

In this note we provide a new partial solution to the Hurwitz existence problem for surface branched covers. Namely, we consider candidate branch data with base surface the sphere and one partition of the degree having length two, and we fully determine which of them are realizable and which are exceptional. The case where the covering surface is also the sphere was solved somewhat recently by Pakovich, and we deal here with the case of positive genus. We show that the only other exceptional candidate data, besides those of Pakovich (five infinite families and one sporadic case), are a well-known very specific infinite family in degree 4 (indexed by the genus of the candidate covering surface, which can attain any value), five sporadic cases (four in genus 1 and one in genus 2), and another infinite family in genus 1 also already known. Since the degree is a composite number for all these exceptional data, our findings provide more evidence for the prime-degree conjecture. Our argument proceeds by induction on the genus and on the number of branching points, so our results logically depend on those of Pakovich, and we do not employ the technology of constellations on which his proof is based., Comment: 37 pages, 21 figures. Incorporated reviewer's suggestions. To appear in Illinois J. Math

The notion of quasi-particles is essential for understanding the behaviour of complex many-body systems. A prototypical example of a quasi-particle, a polaron, is an impurity strongly interacting with a surrounding medium. Fermi polarons, created in a Fermi sea, provide a paradigmatic realization of this concept. As an inherent and important property such quasi-particles interact with each other via modulation of the medium. While quantum simulation experiments with ultracold atoms have significantly improved our understanding of individual polarons, the detection of their interactions has remained elusive in these systems. Here, we report the unambiguous observation of mediated interactions between Fermi polarons consisting of K impurities embedded in a Fermi sea of Li atoms. Our results confirm two landmark predictions of Landau's Fermi-liquid theory: the shift of the polaron energy due to mediated interactions, linear in the concentration of impurities, and its sign inversion with impurity quantum statistics. For weak to moderate interactions between the impurities and the medium, we find excellent agreement with the static (zero-momentum and energy) predictions of Fermi-liquid theory. For stronger impurity-medium interactions, we show that the observed behaviour at negative energies can be explained by a more refined many-body treatment including retardation and molecule formation

We study numerically Anderson localization on lattices that are tree-like except for the presence of one loop of varying length $L$. The resulting expressions allow us to compute corrections to the Bethe lattice solution on i) Random-Regular-Graph (RRG) of finite size $N$ and ii) euclidean lattices in finite dimension. In the first case we show that the $1/N$ corrections to to the average values of observables such as the typical density of states and the inverse participation ratio have prefactors that diverge exponentially approaching the critical point, which explains the puzzling observation that the numerical simulations on finite RRGs deviate spectacularly from the expected asymptotic behavior. In the second case our results, combined with the $M$-layer expansion, predict that corrections destroy the exotic critical behavior of the Bethe lattice solution in any finite dimension, strengthening the suggestion that the upper critical dimension of Anderson localization is infinity. This approach opens the way to the computation of non-mean-field critical exponents by resumming the series of diverging diagrams through the same recipes of the field-theoretical perturbative expansion.

The application of a temperature gradient to an extended system generates an electromotive force that induces an electric current in conductors and a macroscopic polarization in insulators. The ratio of the electromotive force to the temperature difference, usually referred to as the Seebeck coefficient, is often computed using non-equilibrium techniques, such as non-equilibrium molecular dynamics (NEMD). In this paper we argue that thermo-polarization effects in insulating fluids can be conveniently treated by standard equilibrium thermodynamics and devise a protocol, based on a combination of equilibrium molecular dynamics and Bayesian inference methods, that allows one to compute the Seebeck coefficient in these systems along with a rigorous estimate of the resulting statistical accuracy. The application of our methodology to liquid SPC/E water results in good agreement with previous studies, based on more elaborate NEMD simulations, and in a more reliable estimate of the statistical accuracy of the results., Comment: 6 pages, 5 figures

Neural captioners are typically trained to mimic human-generated references without optimizing for any specific communication goal, leading to problems such as the generation of vague captions. In this paper, we show that fine-tuning an out-of-the-box neural captioner with a self-supervised discriminative communication objective helps to recover a plain, visually descriptive language that is more informative about image contents. Given a target image, the system must learn to produce a description that enables an out-of-the-box text-conditioned image retriever to identify such image among a set of candidates. We experiment with the popular ClipCap captioner, also replicating the main results with BLIP. In terms of similarity to ground-truth human descriptions, the captions emerging from discriminative finetuning lag slightly behind those generated by the non-finetuned model, when the latter is trained and tested on the same caption dataset. However, when the model is used without further tuning to generate captions for out-of-domain datasets, our discriminatively-finetuned captioner generates descriptions that resemble human references more than those produced by the same captioner without finetuning. We further show that, on the Conceptual Captions dataset, discriminatively finetuned captions are more helpful than either vanilla ClipCap captions or ground-truth captions for human annotators tasked with an image discrimination task., Comment: CVPR 2023

In the past few years, the theory of thermal transport in amorphous solids has been substantially extended beyond the Allen-Feldman model. The resulting formulation, based on the Green-Kubo linear response or the Wigner-transport equation, bridges this model for glasses with the traditional Boltzmann kinetic approach for crystals. The computational effort required by these methods usually scales as the cube of the number of atoms, thus severely limiting the size range of computationally affordable glass models. Leveraging hydrodynamic arguments, we show how this issue can be overcome through a simple formula to extrapolate a reliable estimate of the bulk thermal conductivity of glasses from finite models of moderate size. We showcase our findings for realistic models of paradigmatic glassy materials., Comment: 15 pages, 5 figures

In preparation for the 2023 NSAC Long Range Plan (LRP), members of the Nuclear Science community gathered to discuss the current state of, and plans for further leveraging opportunities in, QIST in NP research at the Quantum Information Science for U.S. Nuclear Physics Long Range Planning workshop, held in Santa Fe, New Mexico on January 31 - February 1, 2023. The workshop included 45 in-person participants and 53 remote attendees. The outcome of the workshop identified strategic plans and requirements for the next 5-10 years to advance quantum sensing and quantum simulations within NP, and to develop a diverse quantum-ready workforce. The plans include resolutions endorsed by the participants to address the compelling scientific opportunities at the intersections of NP and QIST. These endorsements are aligned with similar affirmations by the LRP Computational Nuclear Physics and AI/ML Workshop, the Nuclear Structure, Reactions, and Astrophysics LRP Town Hall, and the Fundamental Symmetries, Neutrons, and Neutrinos LRP Town Hall communities., Comment: A white paper for the 2023 nuclear physics long-range planning activity, emerging from the workshop "Quantum Information Science for U.S. Nuclear Physics Long Range Planning'', held in Santa Fe, New Mexico on January 31 - February 1, 2023. 26 pages with 7 figures

We study whether automatically-induced prompts that effectively extract information from a language model can also be used, out-of-the-box, to probe other language models for the same information. After confirming that discrete prompts induced with the AutoPrompt algorithm outperform manual and semi-manual prompts on the slot-filling task, we demonstrate a drop in performance for AutoPrompt prompts learned on a model and tested on another. We introduce a way to induce prompts by mixing language models at training time that results in prompts that generalize well across models. We conduct an extensive analysis of the induced prompts, finding that the more general prompts include a larger proportion of existing English words and have a less order-dependent and more uniform distribution of information across their component tokens. Our work provides preliminary evidence that it's possible to generate discrete prompts that can be induced once and used with a number of different models, and gives insights on the properties characterizing such prompts., Comment: Published as conference paper at ICLR 2023

As large pre-trained image-processing neural networks are being embedded in autonomous agents such as self-driving cars or robots, the question arises of how such systems can communicate with each other about the surrounding world, despite their different architectures and training regimes. As a first step in this direction, we systematically explore the task of \textit{referential communication} in a community of heterogeneous state-of-the-art pre-trained visual networks, showing that they can develop, in a self-supervised way, a shared protocol to refer to a target object among a set of candidates. This shared protocol can also be used, to some extent, to communicate about previously unseen object categories of different granularity. Moreover, a visual network that was not initially part of an existing community can learn the community's protocol with remarkable ease. Finally, we study, both qualitatively and quantitatively, the properties of the emergent protocol, providing some evidence that it is capturing high-level semantic features of objects.

The nature of the gap observed at the zone border in the spin-excitation spectrum of CrI$_3$ quasi-2D single crystals is still controversial. We perform first-principles calculations based on time-dependent density-functional perturbation theory, which indicate that the observed gap results from a combination of spin-orbit and inter-layer interaction effects. The former give rise to the anisotropic spin-spin interactions that are responsible for its very existence, while the latter determine both its displacement from the K point of the Brillouin zone due to the in-plane lattice distortions induced by them, and an enhancement of its magnitude, in agreement with experiments and previous theoretical work based on a lattice model.

We present an efficient method to prepare states of a many-body system on quantum hardware, first isolating individual quantum numbers and then using time evolution to isolate the energy. Our method in its simplest form requires only one additional auxiliary qubit. The total time evolved for an accurate solution is proportional to the ratio of the spectrum range of the trial state to the gap to the lowest excited state, and the accuracy increases exponentially with the time evolved. Isolating the quantum numbers is efficient because of the known eigenvalues, and increases the gap thus shortening the propagation time required. The success rate of the algorithm, or the probability of producing the desired state, is a simple function of measurement times and phases and is dominated by the square overlap of the original state to the desired state. We present examples from the nuclear shell model and the Heisenberg model. We compare this algorithm to previous algorithms for short evolution times and discuss potential further improvements.

We consider a dissipative version of the standard nontwist map. Nontwist systems present a robust transport barrier, called the shearless curve, that becomes the shearless attractor when dissipation is introduced. This attractor can be regular or chaotic depending on the control parameters. Chaotic attractors can undergo sudden and qualitative changes as a parameter is varied. These changes are called crises, and at an interior crisis the attractor suddenly expands. Chaotic saddles are nonattracting chaotic sets that play a fundamental role in the dynamics of nonlinear systems, they are responsible for chaotic transients, fractal basin boundaries, chaotic scattering and they mediate interior crises. In this work we discuss the creation of chaotic saddles in a dissipative nontwist system and the interior crises they generate. We show how the presence of two saddles increase the transient times and analyze the phenomenon of crisis induced intermittency.

HERMES (High Energy Rapid Modular Ensemble of Satellites) is a space-borne mission based on a constellation of nano-satellites flying in a low-Earth orbit (LEO). The six 3U CubeSat buses host new miniaturized instruments hosting a hybrid Silicon Drift Detector/GAGG:Ce scintillator photodetector system sensitive to X-rays and gamma-rays. HERMES will probe the temporal emission of bright high-energy transients such as Gamma-Ray Bursts (GRBs), ensuring a fast transient localization (with arcmin-level accuracy) in a field of view of several steradians exploiting the triangulation technique. With a foreseen launch date in late 2023, HERMES transient monitoring represents a keystone capability to complement the next generation of gravitational wave experiments. Moreover, the HERMES constellation will operate in conjunction with the Space Industry Responsive Intelligent Thermal (SpIRIT) 6U CubeSat, to be launched in early 2023. SpIRIT is an Australian-Italian mission for high-energy astrophysics that will carry in a Sun-synchronous orbit (SSO) an actively cooled HERMES detector system payload. On behalf of the HERMES collaboration, in this paper we will illustrate the HERMES and SpIRIT payload design, integration and tests, highlighting the technical solutions adopted to allow a wide-energy-band and sensitive X-ray and gamma-ray detector to be accommodated in a 1U Cubesat volume., Comment: arXiv admin note: substantial text overlap with arXiv:2101.03032

HERMES (High Energy Rapid Modular Ensemble of Satellites) is a space-borne mission based on a constellation of six 3U CubeSats flying in a low-Earth orbit, hosting new miniaturized instruments based on a hybrid Silicon Drift Detector/GAGG:Ce scintillator photodetector system sensitive to X-rays and gamma-rays. Moreover, the HERMES constellation will operate in conjunction with the Australian-Italian Space Industry Responsive Intelligent Thermal (SpIRIT) 6U CubeSat, that will carry in a Sun-synchronous orbit (SSO) an actively cooled HERMES detector system payload. In this paper we provide an overview of the ground calibrations of the first HERMES and SpIRIT flight detectors, outlining the calibration plan, detector performance and characterization., Comment: 9 pages, 7 figures. Proceedings of SPIE Astronomical Telescopes and Instrumentation 2022

We compare the 0-shot performance of a neural caption-based image retriever when given as input either human-produced captions or captions generated by a neural captioner. We conduct this comparison on the recently introduced ImageCoDe data-set (Krojer et al., 2022) which contains hard distractors nearly identical to the images to be retrieved. We find that the neural retriever has much higher performance when fed neural rather than human captions, despite the fact that the former, unlike the latter, were generated without awareness of the distractors that make the task hard. Even more remarkably, when the same neural captions are given to human subjects, their retrieval performance is almost at chance level. Our results thus add to the growing body of evidence that, even when the ``language'' of neural models resembles English, this superficial resemblance might be deeply misleading., Comment: Accepted as a short paper at EMNLP 2022

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing., Comment: Submitted as a roadmap article to Modelling and Simulation in Materials Science and Engineering; Address any correspondence to Vikram Gavini (vikramg@umich.edu) and Danny Perez (danny_perez@lanl.gov)

I present a different approach to Rayleigh-Schr\"odinger perturbation theory, based on Laplace transforms and polynomial theory, yielding an iterative expression for the perturbative expansion of the energy of the non-degenerate ground state of a quantum system, which easily lends itself to symbolic computation. A stochastic interpretation of the various perturbative corrections naturally leads to a re-summation scheme that is equivalent to Reptation Quantum Monte Carlo and that actually provided the original motivation to its development in the late nineties., Comment: 8 pages, no figures. Paper presented at CECAM workshop on "Recent developments in quantum Monte Carlo", Rome, October 21-22, 2021