We employ the joint QED and QCD factorization of deeply inelastic, electron-proton scattering with generic initial state radiation to probe the possibility of exotic particle emission -- i.e., of weakly coupled particles originating from a dark or hidden sector -- through anomalous energy loss. We leverage this possibility through the consideration of phase-space-limited kinematic regions, for which the emission of an additional, undetected particle can particularly impact the associated cross-section. In this first paper, as a proof of principle, we focus on radiation from the incoming electron, considering the modification of the lepton distribution function from the emission of particles, that could have spin of up to 2 and various, well-motivated electron couplings. We illustrate the sensitivity of our approach through the computation of the modified cross-sections for the emission of MeV-GeV mass-scale, spin 0 particles in kinematics chosen for their sensitivity to initial state electron radiation and suitable to the forward-backward detection sensitivity of the ePIC detector at the EIC.
Recent advances in generative artificial intelligence (AI), such as ChatGPT, Google Gemini, and other large language models (LLMs), pose significant challenges for maintaining academic integrity within higher education. This paper examines the structural susceptibility of a certified M.Sc. Cyber Security program at a UK Russell Group university to the misuse of LLMs. Building on and extending a recently proposed quantitative framework for estimating assessment-level exposure, we analyse all summative assessments on the program and derive both module-level and program-level exposure metrics. Our results show that the majority of modules exhibit high exposure to LLM misuse, driven largely by independent project- and report-based assessments, with the capstone dissertation module particularly vulnerable. We introduce a credit-weighted program exposure score and find that the program as a whole falls within a high to very high risk band. We also discuss contextual factors -- such as block teaching and a predominantly international cohort -- that may amplify incentives to misuse LLMs. In response, we outline a set of LLM-resistant assessment strategies, critically assess the limitations
Multiplayer online gaming has witnessed an explosion in popularity over the past two decades. However, security issues continue to give rise to in-game cheating, deterring honest gameplay, detracting from user experience, and ultimately bringing financial harm to game developers. In this paper, we present a new approach for detecting network packet-based cheats, such as forgery and timing cheats, within the context of multiplayer games using an application of secret sharing. Our developed protocols are subjected to formal verification using AVISPA, and we present simulation results using a Python-based implementation. We show that our proposal is practical in addressing some widely used attacks in online gaming.
Mobile sensor data has been proposed for security-critical applications such as device pairing, proximity detection, and continuous authentication. However, the foundational premise that these signals provide sufficient entropy remains under-explored. In this work, we systematically analyse the entropy of mobile sensor data using four datasets from multiple application contexts (UCI-HAR, SHL, Relay, and PerilZIS). Using direct computation and estimation, we report entropy values (max, Shannon, collision, and min-entropy) for an exhaustive range of sensor combinations. We demonstrate that the entropy of mobile sensors remains far below what is considered secure by modern standards for security applications, even when many sensors are combined. In particular, we observe an alarming divergence between average-case Shannon entropy and worst-case min-entropy. Single-sensor min-entropy varies between 3.408-4.483 bits despite Shannon entropy being several multiples higher. We also show that redundancies between sensor modalities contribute to a ~75% reduction between Shannon and min-entropy. Indeed, min-entropy plateaus between 8.1-23.9 bits when combining up to 22 modalities, while Shann
Screened scalars are ubiquitous in many dark-sector models. They give rise to non-trivial fifth forces whilst evading experimental constraints through density-dependent screening mechanisms. We propose equipping a 10\,m-scale long-baseline atom interferometer with an annular planar source mass inside the vacuum chamber to search for such screened fifth forces. Two key challenges arise: distinguishing the static fifth force from backgrounds, and isolating it from the plate's Newtonian gravity. We introduce the `$Q$-flip protocol', which alternates between interferometry sequences to induce controllable time-dependence, aiding signal extraction and de-trending of transient noise. We further develop an \emph{in situ} calibration procedure to characterise the plate's Newtonian gravity and reach shot-noise-limited sensitivity. We show that our proposal could test theoretically motivated parameter space, advancing existing bounds in chameleon and symmetron screened scalar models by $1$ to $1.5$ orders of magnitude. Our proposal is directly applicable to forthcoming experiments, such as AION-10 or VLBAI, and is readily extensible to broader theoretical models and longer baselines.
Atom interferometers offer exceptional sensitivity to ultra-light dark matter (ULDM) by precisely measuring effects on atomic systems. Previous studies have demonstrated their capability to detect scalar and vector ULDM candidates, yet their potential for probing spin-2 ULDM remains unexplored. In this work, we address this gap by investigating the sensitivity of atom interferometers to spin-2 ULDM across several frameworks for massive gravity, including the Lorentz-invariant Fierz-Pauli case and two distinct Lorentz-violating scenarios. We show that coherent oscillations of the spin-2 ULDM field induce measurable phase shifts in atom interferometers through three coupling mechanisms: scalar interactions that modify atomic energy levels, and vector and tensor effects that alter the propagation of both atoms and light. We demonstrate that these multifaceted interactions enable atom interferometers to probe a range of ULDM properties and mass scales that are inaccessible to laser interferometric gravitational wave detectors. Our results establish the potential of atom interferometers to open a new experimental frontier for spin-2 dark matter detection.
We predict the surface density and clustering bias of H$α$ emitting galaxies for the Euclid and Nancy Grace Roman Space Telescope redshift surveys using a new calibration of the GALFORM galaxy formation model. We generate 3000 GALFORM models to train an ensemble of deep learning algorithms to create an emulator. We then use this emulator in a Markov Chain Monte Carlo (MCMC) parameter search of an eleven-dimensional parameter space, to find a best-fitting model to a calibration dataset that includes local luminosity function data, and, for the first time, higher redshift data, namely the number counts of H$α$ emitters. We discover tensions when exploring fits for the observational data when applying a heuristic weighting scheme in the MCMC framework. We find improved fits to the H$α$ number counts while maintaining appropriate predictions for the local universe luminosity function. For a flux limited Euclid-like survey to a depth of 2$\times$10$^{-16}$ erg$^{-1}$ s$^{-1}$ cm$^{-2}$ for sources in the redshift range 0.9 < $z$ < 1.8, we estimate 2962-4331 H$α$ emission-line sources deg$^{-2}$. For a Nancy Grace Roman survey, with a flux limit of 1$\times$10$^{-16}$ erg$^{-1}$ s$
Control-flow attestation unifies the worlds of control-flow integrity and platform attestation by measuring and reporting a target's run-time behaviour to a verifier. Trust assurances in the target are provided by testing whether its execution follows an authorised control-flow path. The problem has been explored in various settings, such as assessing the trustworthiness of cloud platforms, cyber-physical systems, and Internet of Things devices. Despite a significant number of proposals being made in recent years, the area remains fragmented, with different adversarial behaviours, verification paradigms, and deployment challenges being addressed. In this paper, we present the first survey of control-flow attestation, examining the core ideas and solutions in state-of-the-art schemes. In total, we survey over 30 papers published between 2016--2024, consolidate and compare their key features, and pose several challenges and recommendations for future research in the area.
Terrestrial long-baseline atom interferometer experiments are emerging as powerful tools for probing new fundamental physics, including searches for dark matter and gravitational waves. In the frequency range relevant to these signals, gravity gradient noise (GGN) poses a significant challenge. While previous studies for vertical instruments have focused on GGN induced by seismic waves, atmospheric fluctuations in pressure and temperature also lead to variations in local gravity. In this work, we advance the understanding of atmospheric GGN in vertical atom interferometers, formulating a robust characterization of its impact. We evaluate the effectiveness of underground placement of atom interferometers as a passive noise mitigation strategy. Additionally, we empirically derive global high- and low-noise models for atmospheric pressure GGN and estimate an analogous range for atmospheric temperature GGN. To highlight the variability of temperature-induced noise, we compare data from three prospective experimental sites. Our findings establish atmospheric GGN as comparable to seismic noise in its impact and underscore the importance of including these effects in site selection and ac
The canonical commutation relation, $[Q,P] = i\hbar$, stands at the foundation of quantum theory and the original Hilbert space. The interpretation of $P$ & $Q$ as observables has always relied on the analogies that exist between the unitary transformations of Hilbert space and the canonical (a.k.a. contact) transformations of classical phase space. Now that the theory of quantum measurement is essentially complete (this took a while), it is possible to revisit the canonical commutation relation in a way that sets the foundation of quantum theory not on unitary transformations, but on positive transformations. This paper shows how the concept of simultaneous measurement leads to a fundamental differential geometric problem whose solution shows us the following: The simultaneous $P$ & $Q$ measurement (SPQM) defines a universal measuring instrument, which takes the shape of a 7-dimensional manifold, a universal covering group we call the Instrumental Weyl-Heisenberg Group, IWH. The group IWH connects the identity to classical phase space in unexpected ways that are significant enough that the positive-operator-valued measure (POVM) offers a complete alternative to energy quan
Atom interferometers offer promising new avenues for detecting ultra-light dark matter (ULDM). The exceptional sensitivity of atom interferometers to fluctuations in the local gravitational potential exposes them to sources of noise from human (anthropogenic) and animal (synanthropic) activity, which may obscure signals from ULDM. We characterise potential anthropogenic and synanthropic noise sources and examine their influence on a year-long measurement campaign by AION-10, an upcoming atom interferometer experiment that will be located at the University of Oxford. We propose a data cleaning framework that identifies and then masks anthropogenic and synanthropic noise. With this framework, we demonstrate that even in noisy conditions, the sensitivity to ULDM can be restored to within between 10% and 40% of an atom shot noise-limited experiment, depending on the specific composition of the anthropogenic and synanthropic noise. This work provides an important step towards creating robust noise reduction analysis strategies in the pursuit of ULDM detection with atom interferometers.
Digital rights management (DRM) solutions aim to prevent the copying or distribution of copyrighted material. On mobile devices, a variety of DRM technologies have become widely deployed. However, a detailed security study comparing their internal workings, and their strengths and weaknesses, remains missing in the existing literature. In this paper, we present the first detailed security analysis of mobile DRM systems, addressing the modern paradigm of cloud-based content delivery followed by major platforms, such as Netflix, Disney+, and Amazon Prime. We extensively analyse the security of three widely used DRM solutions -- Google Widevine, Apple FairPlay, and Microsoft PlayReady -- deployed on billions of devices worldwide. We then consolidate their features and capabilities, deriving common features and security properties for their evaluation. Furthermore, we identify some design-level shortcomings that render them vulnerable to emerging attacks within the state of the art, including micro-architectural side-channel vulnerabilities and an absence of post-quantum security. Lastly, we propose mitigations and suggest future directions of research.
This paper presents new methods and results for recognising black-box program functions using hardware performance counters (HPC), where an investigator can invoke and measure function calls. Important use cases include analysing compiled libraries, e.g. static and dynamic link libraries, and trusted execution environment (TEE) applications. We develop a generic approach to classify a comprehensive set of hardware events, e.g. branch mis-predictions and instruction retirements, to recognise standard benchmarking and cryptographic library functions. This includes various signing, verification and hash functions, and ciphers in numerous modes of operation. Three architectures are evaluated using off-the-shelf Intel/X86-64, ARM, and RISC-V CPUs. Next, we show that several known CVE-numbered OpenSSL vulnerabilities can be detected using HPC differences between patched and unpatched library versions. Further, we demonstrate that standardised cryptographic functions within ARM TrustZone TEE applications can be recognised using non-secure world HPC measurements, applying to platforms that insecurely perturb the performance monitoring unit (PMU) during TEE execution. High accuracy was achi
We formulate a general program for [...] analyzing continuous, differential weak, simultaneous measurements of noncommuting observables, which focuses on describing the measuring instrument autonomously, without states. The Kraus operators of such measuring processes are time-ordered products of fundamental differential positive transformations, which generate nonunitary transformation groups that we call instrumental Lie groups. The temporal evolution of the instrument is equivalent to the diffusion of a Kraus-operator distribution function defined relative to the invariant measure of the instrumental Lie group [...]. This way of considering instrument evolution we call the Instrument Manifold Program. We relate the Instrument Manifold Program to state-based stochastic master equations. We then explain how the Instrument Manifold Program can be used to describe instrument evolution in terms of a universal cover[,] the universal instrumental Lie group, which is independent [...] of Hilbert space. The universal instrument is generically infinite dimensional, in which situation the instrument's evolution is chaotic. Special simultaneous measurements have a finite-dimensional universa
Quantitative decision-making (QDM) principles address the issues related to the mapping of results to decisions, the synthesis of information and the quantification of uncertainty. Since the clinical drug development involves a succession of decisions to be made, QDM methods can be applied at various levels. At the study level, it can be used to properly design a study, and improve the decisions that are made either during the trial or at its end. Establishing decision criteria ahead of the study is essential here to address the need for speedy decisions, potentially in real time. At the project level, QDM can be used to inform decisions to continue, adapt or stop a drug development programme based on results from previous studies. At the portfolio level, QDM can be used to choose, prioritise and optimise the development portfolio, e.g. using the probability to reach market access or target sales within a predefined timeline. The increasing interest in QDM and its statistical nature led in 2017 to the development a cross-industry and academia Special Interest Group on QDM within the Society and the European Federation of Statisticians in the Pharmaceutical Industry (PSI and EFSPI).
The pharmaceutical industry has experienced increasing costs and sustained high attrition rates in drug development over the last years. One proposal that addresses this challenge from a statistical perspective is the use of quantitative decision-making (QDM) methods to support a data-driven, objective appraisal of the evidence that forms the basis of decisions at different development levels. Growing awareness among statistical leaders in the industry has led to the creation of the European EFSPI/PSI special interest group (ESIG) on quantitative decision making to share experiences, collect best practices, and promote the use of QDM. In this paper, we introduce key components of QDM and present examples of QDM methods on trial, program, and portfolio level. The ESIG created a questionnaire to learn how and to what extent QDM methods are currently used in the different development phases. We present the main questionnaire findings, and we show where QDM is already used today but also where areas for future improvement can be identified. In particular, statisticians should increase their visibility, involvement, and leadership in cross-functional decision-making.
A new study suggests Earth may have been sending tiny hitchhikers to Venus for billions of years。 Researchers found that asteroid impacts could launch microbes into space, where some might survive the journey and end up suspended in Venus' clouds。 If future missions detect life there, there's a surprising chance it didn't originate on Venus at all—
Scientists have uncovered new evidence that fireworks can pollute both the air and water in ways that extend beyond the visible smoke。 The findings show that leftover debris, fine particles, and airborne chemicals may affect ecosystems and increase people's exposure to air pollution during major celebrations
Researchers have proposed that black holes stop evaporating at the last moment, leaving behind tiny remnants that preserve all the information they contain。 The same seven-dimensional geometry behind this idea could also help explain why elementary particles have mass
Two newly confirmed "super-puff" planets are so diffuse that they are less dense than cotton candy, despite being about the size of Jupiter。 Their rare orbital relationship and enormous, lightweight atmospheres could provide valuable clues about how some of the strangest planets in the galaxy come to exist