CyberSec Research

We study magnetic conversion of ultra-relativistic axion-like particles (ALPs) into photons in compact-star environments, focusing on the hot, transient conditions of core-collapse supernova (SN) remnants and neutron-star mergers (NSMs). We address previously overlooked uncertainties, particularly the suppression caused by ejected matter near the stellar surface, a region crucial to the conversion process. We derive analytical expressions for the transition rate; they reveal the influence of key parameters and their uncertainties. We update constraints using historical gamma-ray data from SN~1987A and find $g_{a\gamma}<5\times10^{-12}~{\rm GeV}^{-1}$ for $m_a\lesssim10^{-9}$ meV. We also forecast sensitivities for a future Galactic SN and for NSMs, assuming observations with Fermi-LAT or similar gamma-ray instruments. We distinguish ALPs -- defined as coupling only to photons and produced via Primakoff scattering -- from axions, which also couple to nucleons and emerge through nuclear bremsstrahlung. We omit pionic axion production due to its large uncertainties and inconsistencies, though it could contribute comparably to bremsstrahlung under optimistic assumptions. For the compact sources, we adopt time-averaged one-zone models, guided by numerical simulations, to enable clear and reproducible parametric studies.

We demonstrate that Gaia's detection of stars on wide orbits around black holes opens a new observational window on dark matter structures -- such as scalar clouds and dark matter spikes -- predicted in a range of theoretical scenarios. Using precise radial velocity measurements of these systems, we derive state-of-the-art constraints on dark matter density profiles and particle masses in previously unexplored regions of parameter space. We also test the black hole hypothesis against the alternative of a boson star composed of light scalar fields.

Recent measurements of baryon acoustic oscillations (BAO) from the Dark Energy Spectroscopic Instrument (DESI) have been interpreted to suggest that dark energy may be evolving. In this work, we examine how prior choices affect such conclusions. Specifically, we study the biases introduced by the customary use of uniform priors on the Chevallier-Polarski-Linder (CPL) parameters, $w_0$ and $w_a$, when assessing evidence for evolving dark energy. To do so, we construct theory-informed priors on $(w_0, w_a)$ using a normalizing flow (NF), trained on two representative quintessence models, which learns the distribution of these parameters conditional on the underlying $\Lambda$CDM parameters. In the combined $\textit{Planck}$ CMB + DESI BAO analysis we find that the apparent tension with a cosmological constant in the CPL framework can be reduced from $\sim 3.1\sigma$ to $\sim 1.3\sigma$ once theory-informed priors are applied, rendering the result effectively consistent with $\Lambda$CDM. For completeness, we also analyze combinations that include Type Ia supernova data, showing similar shifts toward the $\Lambda$CDM limit. Taken together, the observed sensitivity to prior choices in these analyses arises because uniform priors - often mischaracterized as "uninformative" - can actually bias inferences toward unphysical parameter regions. Consequently, our results underscore the importance of adopting physically motivated priors to ensure robust cosmological inferences, especially when evaluating new hypotheses with only marginal statistical support. Lastly, our NF-based framework achieves these results by post-processing existing MCMC chains, requiring $\approx 1$ hour of additional CPU compute time on top of the base analysis - a dramatic speedup over direct model sampling that highlights the scalability of this approach for testing diverse theoretical models.

The Vera C. Rubin Observatory LSST is expected to discover tens of millions of new Active Galactic Nuclei (AGNs). The survey's exceptional cadence and sensitivity will enable UV/optical/NIR monitoring of a significant fraction of these objects. The unprecedented number of sources makes spectroscopic follow-up for the vast majority of them unfeasible in the near future, so most studies will have to rely on photometric redshifts estimates which are traditionally much less reliable for AGN than for inactive galaxies. This work presents a novel methodology to constrain the photometric redshift of AGNs that leverages the effects of cosmological time dilation, and of the luminosity and wavelength dependence of AGN variability. Specifically, we assume that the variability can be modeled as a damped random walk (DRW) process, and adopt a parametric model to characterize the DRW timescale ($\tau$) and asymptotic amplitude of the variability (SF$_\infty$) based on the redshift, the rest-frame wavelength, and the AGN luminosity. We construct variability-based photo-$z$ priors by modeling the observed variability using the expected DRW parameters at a given redshift. These variability-based photometric redshift (VAR-PZ) priors are then combined with traditional SED fitting to improve the redshift estimates from SED fitting. Validation is performed using observational data from the SDSS, demonstrating significant reduction in catastrophic outliers by more than 10% in comparison with SED fitting techniques and improvements in redshift precision. The simulated light curves with both SDSS and LSST-like cadences and baselines confirm that, VAR-PZ will be able to constrain the photometric redshifts of SDSS-like AGNs by bringing the outlier fractions down to below 7% from 32% (SED-alone) at the end of the survey.

We demonstrate a GPU-accelerated nested sampling framework for efficient high-dimensional Bayesian inference in cosmology. Using JAX-based neural emulators and likelihoods for cosmic microwave background and cosmic shear analyses, our approach provides parameter constraints and direct calculation of Bayesian evidence. In the 39 dimensional $\Lambda$CDM vs $w_0w_a$ shear analysis, we produce Bayes Factors and a robust error bar in just 2 days on a single A100 GPU, without loss of accuracy. Where CPU-based nested sampling can now be outpaced by methods relying on MCMC sampling and decoupled evidence estimation, we demonstrate that with GPU acceleration nested sampling offers the necessary speed-up to put it on equal computational footing with these methods, especially where reliable model comparison is paramount. We put forward both nested and gradient-based sampling as useful tools for the modern cosmologist, where cutting-edge inference pipelines can yield orders of magnitude improvements in computation time.

In this work we examine the 2025 DESI analysis of dark energy, which suggests that dark energy is evolving in time with an increasing equation of state $w$. We explore a wide range of quintessence models, described by a potential function $V(\varphi)$, including: quadratic potentials, quartic hilltops, double wells, cosine functions, Gaussians, inverse powers. We find that while some provide improvement in fitting to the data, compared to a cosmological constant, the improvement is only modest. We then consider non-minimally coupled scalars which can help fit the data by providing an effective equation of state that temporarily obeys $w<-1$ and then relaxes to $w>-1$. Since the scalar is very light, this leads to a fifth force and to time evolution in the effective gravitational strength, which are both tightly constrained by tests of gravity. For a very narrow range of carefully selected non-minimal couplings we are able to evade these bounds, but not for generic values.

Recently, two of the present authors showed that even when the axion momentum is much smaller than its mass, the axion can still behave like radiation if its energy density greatly exceeds the maximum potential energy set by the cosine-type potential. As the energy density redshifts down to the potential scale, a nonlinear transition occurs, during which the axion's adiabatic invariant is not conserved. In this paper, we revisit the analysis of axion dark matter by incorporating the effects of this nonlinear transition through a precise study of the axion spectrum. We demonstrate that in the parameter region with a relatively small decay constant, often favored in axion search experiments, special care is required when estimating the axion abundance and spectrum. We also highlight a scenario in which axions are produced through the stimulated decay of a modulus, a situation that may naturally arise in the string axiverse, where the nonlinear transition occurs across a wide parameter region. Furthermore, we discuss related phenomena, including QCD axion dark matter, the formation of axion clumps such as miniclusters and axion stars, gravitational wave production, and formation of primordial black holes as dark matter.

DES-5Y supernovae, combined with DESI BAO, appear to favour Chevallier-Polarski-Linder $(w_0, w_a)$ dynamical dark energy over $\Lambda$CDM. arXiv:2408.07175 suggested that this is driven by a systematic in the DES pipeline, which particularly affects the low-redshift supernovae brought in from legacy surveys. It is difficult to investigate these data in isolation, however, as the complicated supernovae pipelines must properly account for selection effects. In this work, we discover that the Bayesian evidence previously found for flexknot dark energy (arXiv:2503.17342) is beaten by a magnitude offset between the low- and high-redshift supernovae. In addition, we find that the possible tension between DES-5Y and DESI is significantly reduced by such an offset. We also take the opportunity to trial Nested Bridge Sampling with Sequential Monte Carlo as an alternative method for calculating Bayes factors.

Detecting parity violation on cosmological scales would provide a striking clue to new physics. Large-scale structure offers the raw statistical power -- many three-dimensional modes -- to make such tests. However, for scalar observables, like galaxy clustering, the leading parity-sensitive observable is the trispectrum, whose high dimensionality makes the measurement and noise estimation challenging. We present two late-time parity-odd kurto spectra that compress the parity-odd scalar trispectrum into one-dimensional, power-spectrum-like observables. They are built by correlating (i) two appropriately weighted quadratic composite fields, or (ii) a linear and cubic composite field, constructed from dark matter (DM) or galaxy overdensity fields. We develop an FFTLog pipeline for efficient theoretical predictions of the two observables. We then validate the estimators for a specific parity-odd primordial template on perturbative DM field, and on DM and halo fields in full N-body \texttt{Quijote} simulations, with and without parity-odd initial conditions, in real and redshift space. For DM, the variance is dominated by the parity-even contribution -- i.e., the gravitationally induced parity-even trispectrum -- and is efficiently suppressed by phase-matched fiducial subtraction. For halos, discreteness-driven stochasticity dominates and is not appreciably reduced by subtraction; however, optimal weighting and halo-matter cross kurto spectra considerably mitigate this noise and enhance the signal. Using controlled down-sampling of the matter field, we empirically calibrate how the parity-even variance scales with number density and volume, and provide an illustrative forecast for the detectability of parity-odd kurto spectra in a Euclid-like spectroscopic galaxy survey.

We show that a simple supersymmetric $U(1)_{B-L}$ extension of the standard model can explain simultaneously the large electron neutrino asymmetry hinted by the recent EMPRESS data as well as the observed tiny baryon number asymmetry via the resonant leptogenesis mechanism. The condensation of $B-L$ Higgs dominating the universe at its decay is the sole source for these generation processes. Here, the infrequent decays of the $B-L$ Higgs to heavy right handed neutrinos and successive prompt decays of these right handed neutrinos around the electroweak phase transition produce the observed baryon number asymmetry, while the complete decay of the same $B-L$ Higgs at a later epoch leads to a large lepton number asymmetry. The right amounts of both asymmetries are found to be obtained for the symmetry-breaking scale $v_\phi \sim 10^{10}~{\rm GeV}$. Moreover, in a close connection to the positivity of both asymmetries, seemingly only the normal mass hierarchy of light neutrino species works. Finally, the gravitational wave background from the topologically stable strong type-I cosmic strings, generated from the breaking of $U(1)_{B-L}$ symmetry, can be within the reach of future experiments such as ultimate DECIGO.

To achieve the sensitivity required to detect signals from neutral hydrogen from the Cosmic Dawn and Epoch of Reionisation it is critical to have a well-calibrated instrument which has a stable calibration over the course of the observation. Previous calibration methods do not explicitly use the time information available and make assumptions on the impedance matching of the reference sources. Here we present a new calibration method based on noise wave parameters which fits a calibration solution over time and frequency to the data, interpolating the solutions to the times at which the antenna is being measured. To test this method we simulate a dataset using measurements of the REACH receiver, modelling a low noise amplifier which is drifting over time. Fitting a polynomial surface in frequency and time to the simulated data demonstrates that we can remove the drift in the calibrated solution over time but leaves a chromatic residual. We further show that we can remove assumptions on the reflection coefficients of the reference noise source and the cold load, reducing degeneracies in the parameter fits. Applying this new calibration equation and surface fitting method to the simulated data removes the chromatic residual in the calibrated spectrum and recovers the parameters to within 0.06% of the truth and a 97% reduction in the RMSE of the spectrum of the validation source compared with previous calibration methods. For two parameters we report up to six times smaller fit error after the degeneracies are removed from the time-based calibration.

The GeV $\gamma$-ray excess observed towards the Galactic Centre remains unexplained. While dark matter annihilation has long been considered a leading interpretation, an alternative scenario involving a large population of millisecond pulsars has not been ruled out. Testing this hypothesis with electromagnetic observations is difficult, as pulsar searches in the bulge are strongly affected by scattering, high sky temperature, and source confusion. We investigate whether gravitational-wave observations with the Laser Interferometer Space Antenna (LISA) could provide an independent probe of the millisecond pulsar binary population in the Galactic bulge. We construct synthetic populations of millisecond pulsar-white dwarf binaries under two illustrative formation scenarios: an accreted scenario, in which systems are deposited by disrupted globular clusters, and an in situ scenario, in which binaries form through isolated binary evolution. In both cases, only $10^{-5}$--$10^{-4}$ of the underlying bulge population is detectable by LISA. Nevertheless, even a few detections would imply tens to hundreds of thousands of unseen systems. Accreted binaries are expected to have lower chirp masses ($\sim$0.4 M$_\odot$), while in situ binaries produce more massive companions ($\sim$0.9 M$_\odot$). LISA will measure binary frequencies with high precision, but chirp masses can only be determined for the most massive or highest-frequency systems. Distinguishing millisecond pulsar binaries from the far more numerous double white dwarfs will be challenging, though LISA detections could provide valuable targets for follow-up with the Square Kilometre Array, enabling a critical test of the millisecond pulsar origin of the $\gamma$-ray excess.

The field of gravitational wave (GW) detection is progressing rapidly, with several next-generation observatories on the horizon, including LISA. GW data is challenging to analyze due to highly variable signals shaped by source properties and the presence of complex noise. These factors emphasize the need for robust, advanced analysis tools. In this context, we have initiated the development of a low-latency GW detection pipeline based on quantum neural networks (QNNs). Previously, we demonstrated that QNNs can recognize GWs simulated using post-Newtonian approximations in the Newtonian limit. We then extended this work using data from the LISA Consortium, training QNNs to distinguish between noisy GW signals and pure noise. Currently, we are evaluating performance on the Sangria LISA Data Challenge dataset and comparing it against classical methods. Our results show that QNNs can reliably distinguish GW signals embedded in noise, achieving classification accuracies above 98\%. Notably, our QNN identified 5 out of 6 mergers in the Sangria blind dataset. The remaining merger, characterized by the lowest amplitude, highlights an area for future improvement in model sensitivity. This can potentially be addressed using additional mock training datasets, which we are preparing, and by testing different QNN architectures and ansatzes.

I revisit whether black-hole remnants, from sub-Planckian compact objects to Planck relics and up to (super)massive black holes, can preserve Standard-Model (SM) electric charge. Two exterior-field mechanisms -- Coulomb-focused capture from ambient media and QED Schwinger pair production -- robustly neutralize such objects across cosmic history. I first derive the general capture rate including both Coulomb and gravitational focusing, and sum the stepwise discharge time in closed form via the trigamma function, exhibiting transparent Coulomb- and gravity-dominated limits. I then integrate the Schwinger rate over the near-horizon region to obtain an explicit $\dot Q(Q)$ law: discharge proceeds until the horizon field falls below $E_{\rm crit}$, leaving a residual charge $Q_{\rm stop}^{(e)}\!\propto\! r_h^2$ that is $\ll e$ for Planck radii. Mapping the mass dependence from sub-Planckian to astrophysical scales, I also analyze dark-sector charges with heavy carriers (including kinetic mixing and massive mediators). In a conservative ``no-Schwinger'' limit where vacuum pair creation is absent, cumulative ambient exposures alone force discharge of any integer SM charge. Three possible loopholes remain. (i) A fine-tuned SM corner in which the relic sits arbitrarily close to Reissner-Nordstr\"om extremality so greybody factors suppress charged absorption, while Schwinger pair creation is absent due to Planck-scale physics. (ii) Charge relocated to a hidden $U(1)_D$ with no light opposite carriers, e.g. if the lightest state is very heavy and/or kinetic mixing with $U(1)_{\rm EM}$ is vanishingly small. (iii) Discrete or topological charges rather than ordinary SM electric charge. Outside these cases, the conclusion is robust: within SM electromagnetism, charged black-hole relics neutralize efficiently and cannot retain charge over cosmological times.

The nature of dark energy remains one of the most important unanswered problems in physics. Here we use gamma-ray spectra from the Type Ia supernova 1991T to constrain the recent evolution of a dynamical pseudoscalar quintessence-like field $Q(t)$. We found that the 1991T gamma rays emitted by the $^{56}\text{Fe}$ nuclei observed by COMPTEL aboard the Compton Gamma Ray Observatory were slightly shifted to lower energies with respect to terrestrial values, with the average fractional energy shift of both the first and second excited states found to be $\delta E/E = -0.006\pm0.008$ including statistical and systematic errors. Assuming that this energy shift is caused by a dynamical QCD axion-like pseudoscalar field $Q(t)$, we find that observed energy deviations are consistent with a fractional rate of change of the pion mass given by $\delta \dot{m_{\pi}}/m_{\pi}=-(6\pm9)\times10^{-11}\text{ yr}^{-1}$. The observed energy deviation was also used to determine the rate of change of the quintessence-like field ($\dot{Q}_0$) for tracking models: $\dot{Q}_{0,max} = (3\pm 4)\times10^7 \text{ GeV/yr}$. Our findings are consistent with the cosmological constant ($\dot{Q}_0 =0$). Furthermore, we have demonstrated how nuclear spectra produced by astrophysical events can be used to inform the nature and behavior of dark energy.

We study the production of primordial gravitational waves (GWs) from first-order phase transitions (FOPTs) in extensions of the Standard Model based on Flavour Deconstruction (FD). The link fields inherent to FD generically form a rich scalar sector, with sizeable couplings at the TeV scale, providing natural conditions for strong FOPTs and correspondingly large GW emission. We identify the key parameters controlling the GW spectrum and enabling its detection at future GW observatories. In particular, we find that while FD scenarios can yield detectable signals, the resulting spectra typically peak at higher frequencies than the millihertz range. As a consequence, a positive observation at LISA is possible but not guaranteed, while the signal falls in the range of mid-band proposals, making FD models an intriguing target for upcoming GW searches.

Stellar collisions in dense galactic nuclei might play an important role in fueling supermassive black holes (SMBHs) and shaping their environments. The gas released during these collisions can contribute to SMBH accretion, influencing phenomena such as active galactic nuclei and tidal disruption events of the remnants. We address the challenge of rapidly and accurately predicting the outcomes of stellar collisionsincluding remnant masses and unbound gasacross a broad parameter space of initial conditions. Existing smoothed-particle-hydrodynamic (SPH) simulation techniques, while detailed, are too resource-intensive for exploratory studies or real-time applications. We develop a machine learning framework trained on a dataset of $\sim 16,000$ SPH simulations of main-sequence star collisions. By extracting physically meaningful parameters (e.g., masses, radii, impact parameters, and virial ratios) and employing gradient-boosted regression trees with Huber loss, we create a model that balances accuracy and computational efficiency. The method includes logarithmic transforms to handle dynamic ranges and regularization to ensure physical plausibility. The model achieves predictions of collision outcomes (remnant masses, and unbound mass) with very low mean absolute errors respect to the typical mass scale. It operates in fractions of a second, enabling large-scale parameter studies and real-time applications. Parameter importance analysis reveals that the impact parameter and the relative velocity dominate outcomes, aligning with theoretical expectations. Our approach provides a scalable tool for studying stellar collisions in galactic nuclei. The rapid predictions facilitate investigations into gas supply for SMBH accretion and the cumulative effects of collisions over cosmic time, particularly relevant to address the growth of SMBHs.

We develop a two-scalar field quintom model, which utilises both a quintessence-like and a phantom-like scalar field, enabling a smooth and stable transition across the $w=-1$ phantom divide as hinted by recent measurements of Baryonic Acoustic Oscillations (BAO) by the Dark Energy Spectroscopic Instrument (DESI) Data Release 2. We explore a range of initial conditions and potential configurations that facilitate such a phantom-to-quintessence-like crossing, and find that this can be naturally realised with hill-top or cliff-face potentials bound from above. We study how varying these conditions affects the dynamics of the system, calculate the background observables and compare them with DESI, CMB, and Type Ia supernova data, identifying a viable parameter space for our model. In particular, we find that a potential featuring a hyperbolic tangent form can successfully reproduce the desired phantom crossing, although such models can suffer from fine-tuning effects. Finally, we discuss prospects for distinguishing such models with upcoming state-of-the-art cosmological observations.