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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