The 100 years since the publication of Albert Einstein’s theory of general relativity saw significant development of the understanding of the theory, the identification of potential astrophysical sources of sufficiently strong gravitational waves and development of key technologies for gravitational-wave detectors. In 2015, the first gravitational-wave signals were detected by the two US Advanced LIGO instruments. In 2017, Advanced LIGO and the European Advanced Virgo detectors pinpointed a binary neutron star coalescence that was also seen across the electromagnetic spectrum. The field of gravitational-wave astronomy is just starting, and this Roadmap of future developments surveys the potential for growth in bandwidth and sensitivity of future gravitational-wave detectors, and discusses the science results anticipated to come from upcoming instruments. In the past few years, gravitational-wave observations provided stunning insights into some of the most cataclysmic events in the Universe, heralding a bright future for gravitational-wave physics and astronomy. This is a Roadmap for the field in the coming two decades. Gravitational-wave observations of binary black hole and neutron star mergers by LIGO and Virgo in the past five years have opened a completely new window on the Universe. The gravitational-wave spectrum, extending from attohertz to kilohertz frequencies, provides a fertile ground for exploring many fundamental questions in physics and astronomy. Pulsar timing arrays currently probe the nanohertz to microhertz frequency band to detect gravitational-wave remnants from past mergers of super-massive black holes. The space-based Laser Interferometer Space Antenna (LISA) will target gravitational-wave sources from microhertz up to hundreds of millihertz and trace the evolution of black holes from the early Universe through the peak of the star formation era. Einstein Telescope and Cosmic Explorer, two future ground-based observatories now under development for the 2030s, are pursuing new technologies to achieve a tenfold increase increase in sensitivity to study compact object evolution to the beginning of the star formation era. Gravitational-wave observations of binary black hole and neutron star mergers by LIGO and Virgo in the past five years have opened a completely new window on the Universe. The gravitational-wave spectrum, extending from attohertz to kilohertz frequencies, provides a fertile ground for exploring many fundamental questions in physics and astronomy. Pulsar timing arrays currently probe the nanohertz to microhertz frequency band to detect gravitational-wave remnants from past mergers of super-massive black holes. The space-based Laser Interferometer Space Antenna (LISA) will target gravitational-wave sources from microhertz up to hundreds of millihertz and trace the evolution of black holes from the early Universe through the peak of the star formation era. Einstein Telescope and Cosmic Explorer, two future ground-based observatories now under development for the 2030s, are pursuing new technologies to achieve a tenfold increase increase in sensitivity to study compact object evolution to the beginning of the star formation era.
The nature of dark matter and properties of neutrinos are among the most pressing issues in contemporary particle physics. The dual-phase xenon time-projection chamber is the leading technology to cover the available parameter space for weakly interacting massive particles, while featuring extensive sensitivity to many alternative dark matter candidates. These detectors can also study neutrinos through neutrinoless double-beta decay and through a variety of astrophysical sources. A next-generation xenon-based detector will therefore be a true multi-purpose observatory to significantly advance particle physics, nuclear physics, astrophysics, solar physics, and cosmology. This review article presents the science cases for such a detector.
Matthew R. Buckley, Peizhi Du, Nicolas Fernandez
et al.
Current cosmological data are well-described by the Lambda-Cold Dark Matter (ΛCDM) model, which assumes adiabatic initial conditions for the primordial density perturbations. This agreement between data and theory enables strong constraints on new physics that generates isocurvature perturbations. Existing constraints typically assume a simple power law form for the isocurvature power spectrum. However, many new physics scenarios — such as cosmological phase transitions and gravitational particle production — can deviate from this assumption. To derive general constraints which apply to a wide variety of new physics scenarios, we consider four types of isocurvature modes (dark matter, baryon, dark radiation and neutrino density isocurvature) and parametrize the isocurvature power spectrum using two general forms: a delta function and a broken power law. Using data from the cosmic microwave background (CMB), baryon acoustic oscillations, the Lyman-α forest, and CMB spectral distortions, we place constraints on the isocurvature power spectrum across a wide range of scales, from 10-4 Mpc-1 to 104 Mpc-1.
We perform a model-independent reconstruction of the cosmic distances using the multi-task Gaussian process framework as well as knot-based spline techniques with Dark Energy Spectroscopic Instrument (DESI)-DR2 baryon acoustic oscillation (BAO) and DES-SN5YR datasets. We calibrate the comoving sound horizon at the baryon drag epoch rd to the Planck value, ensuring consistency with early-Universe physics. With the reconstructed cosmic distances and their derivatives, we obtain seven characteristic redshifts in the range 0.3⩽z⩽1.7. We derive the normalized expansion rate of the Universe E(z) at these redshifts. Our findings reveal a significant deviations of approximately 4–5σ from the Planck 2018 cold dark matter Λcold dark matter predictions, particularly pronounced in the redshift range z∼0.35–0.55. These anomalies are consistently observed across both reconstruction methods and combined datasets, indicating robust late-time tensions in the expansion rate of the Universe and which are distinct from the existing ‘Hubble Tension’. This could signal new physics beyond the standard cosmological framework at this redshift range. Our findings underscore the role of characteristic redshifts as sensitive indicators of expansion rate anomalies and motivate further scrutiny with forthcoming datasets from DESI-5YR BAO, Euclid, and LSST. These future surveys will tighten constraints and will confirm whether these late-time anomalies arise from new fundamental physics or unresolved systematics in the data.
Gabriele Montefalcone, B. Wallisch, Katherine Freese
The cosmic neutrino background and other light relics leave distinct imprints in the cosmic microwave background anisotropies through their gravitational influence. Since neutrinos decoupled from the primordial plasma about one second after the big bang, they have been free-streaming through the universe. This induced a characteristic phase shift in the acoustic peaks as a unique signature. In this work, we constrain the free-streaming nature of these relativistic species and other light relics beyond the Standard Model of particle physics by establishing two complementary template-based approaches to robustly infer the size of this phase shift from the temperature and polarization power spectra. One template shifts the multipoles in these spectra, while the other novel template more fundamentally isolates the phase shift at the level of the underlying photon-baryon perturbations. Applying these methods to Planck data, we detect the neutrino-induced phase shift at about 10σ significance, which rises to roughly 14σ with additional data from the Atacama Cosmology Telescope and the South Pole Telescope. We also infer that the data is consistent with the Standard Model prediction of three free-streaming neutrinos. In addition, we forecast the capabilities of future experiments which will enable significantly more precise phase-shift measurements, with the Simons Observatory and CMB-S4 reducing the 1σ uncertainties to roughly 4.3% and 2.5%, respectively. More generally, we establish a new analysis pipeline for the phase shift induced by neutrinos and other free-streaming dark radiation which additionally offers new avenues for exploring physics beyond the Standard Model in a signature-driven and model-agnostic way.
We study the implications of precision measurements of light-element abundances, in combination with the Cosmic Microwave Background, for scenarios of physics beyond the Standard Model that generate large inhomogeneities in the baryon-to-photon ratio. We show that precision Big Bang Nucleosynthesis (BBN) places strong constraints on any mechanism that produces large-scale inhomogeneities at temperatures around or below the TeV scale. In particular, we find that fluctuations of order 25% on comoving length scales larger than the horizon at T ≃ 3 TeV are incompatible with the observed light-element abundances. This sensitivity to early-universe physics arises because baryon-number inhomogeneities homogenize primarily through diffusion, a slow process. As a result, BBN serves as a novel probe of baryogenesis below the TeV scale, readily ruling out some proposed scenarios in the literature. We discuss the implications for electroweak baryogenesis, and further show that precision BBN provides a new probe of first-order phase transitions that generate gravitational waves in the pHz–mHz frequency range. This yields constraints on the electroweak phase transition, as well as first-order phase transitions that have been suggested as an explanation of the pulsar timing array signal. Finally, we comment on the future prospects for improving this probe.
This research focuses on earthquake risk zoning in the Kashan region of central Iran—an area with significant seismic activity due to its location along major fault lines. Central Iran is bordered to the east by the Lut Block, to the north by the Alborz mountain range, and to the south by the Sanandaj-Sirjan region, forming the Iranian plateau. The study area, located in Isfahan province approximately 100 kilometers from Kashan, lies within the structural zones of the elevated Zagros, Sanandaj-Sirjan, and the volcanic arc of Urmia-Dokhtar. The study aims to enhance understanding of seismic hazards and improve risk assessment methodologies. Key findings include the identification of historical earthquakes, which underscore the region's vulnerability. Advanced probabilistic seismic hazard assessment techniques were employed using the OpenQuake platform to model seismic risks effectively. This research is novel in its integration of historical data with modern probabilistic modeling, providing a comprehensive framework for assessing seismic hazards in an underexplored region. Results indicate that while some areas exhibit low seismic activity, the potential for future earthquakes remains significant, highlighting the need for updated hazard assessments. A critical finding is the extended intervals associated with major earthquakes, which may lead to an underestimation of seismic risk. Additionally, the analysis of fault systems reveals complex interactions that influence the seismic behavior of Kashan, providing insights for urban planning and disaster preparedness. Ultimately, this research aims to inform local authorities and stakeholders about seismic risks, enabling effective mitigation strategies and enhancing community resilience against potential disasters.
Abstract Complex nonlinear relationships exist between the permafrost thermal state, active layer thickness, and terrestrial carbon cycle dynamics. In Arctic and boreal Alaska, significant uncertainties characterize the spatiotemporal rate and magnitude of permafrost degradation and the permafrost carbon feedback, with increasing recognition of the importance of thawing mechanisms. The challenges of monitoring sub‐surface phenomena with remote sensing technology further complicate the issue. There is an urgent need to understand how and to what extent thawing permafrost destabilizes the carbon balance in Alaska and to characterize the feedback involved. In this research, we use our artificial intelligence‐driven model GeoCryoAI to quantify permafrost carbon dynamics in Alaska. The GeoCryoAI model uses a hybridized process‐constrained ensemble learning framework to simultaneously ingest, scale, and analyze in situ measurements, remote sensing observations, and process‐based modeling outputs with disparate spatiotemporal sampling and data densities. We evaluated prior naïve (a) persistence and (b) teacher forcing approaches relative to (c) time‐delayed GeoCryoAI simulations, yielding the following error metrics (RMSE) for active layer thickness (ALT), methane (CH4), and carbon dioxide (CO2), respectively: 1.997, 1.327, 1.007 cm [1963–2022]; 0.884, 0.715, 0.694 nmol CH4km−2 month−1 [1994–2022]; 1.906, 0.697, 0.213 µmol CO2km−2 month−1 [1994–2022]. Our approach overcomes traditional model inefficiencies and resolves spatiotemporal disparities. GeoCryoAI captures abrupt and persistent changes while introducing a novel methodology for assimilating contemporaneous information at various scales. We describe GeoCryoAI, the methodology, our results, and plans for future applications.
Geophysics. Cosmic physics, Information technology
The origin of ultra-high-energy cosmic rays (UHECRs) is one of the most intriguing mysteries in astroparticle physics and high-energy physics. Since UHECRs with light mass compositions are less deflected by the Galactic and extragalactic magnetic fields, their arrival directions are more strongly correlated with their origins. Charged-particle astronomy with UHECRs is hence a potentially viable probe of extremely energetic phenomena in the universe. The Global Cosmic Ray Observatory (GCOS) is a proposed next-generation observatory to elucidate these origins through precise measurements of UHECRs with unprecedented exposure and mass identification capabilities. We will focus on the ideas and requirements for GCOS summarized in arXiv:2502.05657 and share the recent advances in detector developments and future perspectives with interdisciplinary research.
Juan Carlos Díaz-Vélez, Riya Yogesh Kore, Paolo Desiati
et al.
We present preliminary results on an updated full-sky analysis of the cosmic-ray arrival direction distribution with data collected by the High-Altitude Water Cherenkov (HAWC) Observatory and IceCube Neutrino Observatory with complementary field of views covering a large fraction of the sky. This study extends the energy range to higher energies. The HAWC Observatory, located at 19$^{\circ}$N has analyzed 8 years of cosmic-ray data over an energy range between 3.0 TeV and 1.0 PeV and confirms an energy-dependent anisotropy in the arrival direction distribution of cosmic rays seen by other experiments. Combined with recently published results from IceCube with 12 years of data, the combined sky maps with 93\% coverage of the sky -- between 70$^{\circ}$N and 90$^{\circ}$S -- and the corresponding angular power spectra largely eliminate biases that result from partial sky coverage.
There are various magnetic field waves with frequencies ranging from mHz to thousands of Hz in the Earth's magnetosphere. These waves can be categorized into three classes depending on their period: ULF (mHz to ~ Hz), ELF (~ Hz to hundreds of Hz), and VLF (hundreds of Hz to thousands of Hz). The regular and continuous ultra-low-frequency (ULF) waves in the magneto-sphere, ranging from 1 mHz to a few Hz, are important to geomagnetic micropulsations. Recently, whistler mode waves generated by lightning and extremely low-frequency (ELF) bursts, which can be attributed to earthquakes, were detected near the surface; their frequencies range from several Hz to a few hundred Hz. The research on the characteristics of ionospheric plasma disturbance caused by the known ground-based very low frequency (VLF) transmitters, whose frequencies range from a few hundred to a few thousand Hz, is of great significance for analyzing changes in the ionospheric environment. These magnetic field waves are crucial for studying various space physical phenomena. As the wave monitoring equipment of global geomagnetic stations measures relative changes and a lack of unified calibration, they cannot conduct joint observations from high to low latitudes and unified comparative studies of the observational data from multiple sensors. The magnetoresistance sensor (ULF: 0.1 mHz–2 Hz), giant magneto-inductance sensor (ELF: 0.2 Hz–2 kHz), and coil sensor (VLF: 0.2–10 kHz) is used to develop a new generation of broadband geomagnetic wave monitors, which are placed on the geomagnetic stations in typical areas such as Mohe (high latitude), Beijing's Ming Tombs (middle latitude), and Sanya Ledong (low latitude), near the 120° meridian chain. Combined with the data of near-Earth space satellites such as FY-3E and SMILE, the observation ability of various wave phenomena in the Earth's magnetosphere will be comprehensively improved. The performance test experiment shows that the developed wave monitor can detect the fluctuating magnetic field at a particular frequency (1 mHz–10 kHz); magnetic field detection ranges of: ± 65000 nT (ULF frequency band), ± 1000 nT (ELF frequency band), and ± 100 pT (VLF band); with low nonlinear errors: ULF frequency band ≤ 0.0446 %, ELF frequency band ≤0.51 %, and VLF frequency band ≤ 1.18 %; and low noise levels: RMS ≤0.5554 nT (ULF frequency band), NPS ≤0.028 nT /√Hz (ELF frequency band), and NPS ≤0.24 pT/√Hz (VLF band). These characteristics enable the proposed broadband geomagnetic wave monitor to meet the Phase II of Chinese Meridian Project magnetic field detection requirements.
Ndifreke I. Udosen, Aniekan M. Ekanem, Nyakno J. George
Leachate contamination was investigated with geo-electrical methodologies at a major open dump in Eket, Southern Nigeria. The open dump is heavily polluted, degrades the environment, and has released toxins into the atmosphere. To model leachate percolation, vertical electrical soundings (VES) and electrical resistivity tomography (ERT) surveys, constrained by well lithological information, were undertaken at the site. The field equipment used for the geo-electrical investigations was the ABEM Terrameter SAS 1000 and its accessories. WINRESIST software was employed to process the sounding data and RES2DINV was employed to generate 2D tomograms indicating subsurface heterogeneity. Results obtained from sounding data showed that the subsurface had three lithological units (motley topsoil, fine sand and coarse sand), with coarse sand being the main hydrogeological unit comprising water-bearing formations. The first layer’s resistivity ranged from 84.9 – 625.4 Ωm with a mean of 360.4 Ωm; the second layer’s resistivity ranged from 7.5 – 1008.1 Ωm with a mean of 142.9 Ωm, and the third layer’s resistivity values ranged from 11.6 – 745.6 Ωm with a mean of 205.5 Ωm. The 2D resistivity tomograms indicated that leachate had percolated into groundwater resources. This is concerning as groundwater is the major water resource within the area. Measures of the Dar-Zarrouk indices and electrical reflection co-efficient indicated that the highly heterogenous region had moderate aquifer protective capacity and moderate aquifer potentiality. To mitigate contamination at the site, sanitary landfills, phyto-remediation, impermeable liners, or impermeable earth materials should be employed to diminish the rate of leachate percolation.
The Biochemical Methane Potential (BMP) assay is a vital tool for quantifying the amount of methane that specific biodegradable materials can generate in landfills and similar anaerobic environments. Applications of the protocol are extensive and while simple in design, the BMP assay can use anaerobic seed from many different types of sources to determine the methane potential from most biodegradable substrates. Many researchers use differing protocols for this assay, both including and excluding the use of synthetic growth medias, intended to provide vital nutrients and trace elements that facilitate methanogenesis and leave the substrate being tested as the only limiting factor in methane generation potential. The variety of previous approaches inspired this effort to determine the efficacy of adding synthetic growth media to BMP assays. The presented findings suggest the use of M-1 synthetic growth media, defined in this study, at a volumetric ratio of 10% active sludge: 90% M-1 media yielded optimal results in terms of gas yield and reduced variability.
Dams are important water conservation hubs; however, dam locations provided by open datasets are often unreliable. The aim of this article is to provide a single, geographic location-reliable dataset of dams for the scientific community by fusing existing dam datasets and verifying these locations. Using Southeast Asia as the case study, we propose an efficient and automatic method to verify dam locations and developed a process framework. First, the possible location of a dam was obtained by analyzing its geographic location characteristics. Then, the deep learning method was used to detect dams. Finally, a variety of geographic knowledge was applied to comprehensively verify the detection results to obtain accurate and reliable dam location information. The fused dam dataset we produced includes the locations of 4493 dams in Southeast Asia, which were verified using the proposed framework. The verification results were then evaluated via manual visual inspection. The verification accuracy of the framework was 86.7%. The experimental results show that the proposed framework can quickly and reliably verify dam spatial locations and provide solutions for the spatial location verification of other remote sensing objects.
Giacomo Fontanelli, Alessandro Lapini, Leonardo Santurri
et al.
Early-season crop mapping provides decision-makers with timely information on crop types and conditions that are crucial for agricultural management. Current satellite-based mapping solutions mainly rely on optical imagery, albeit limited by weather conditions. Very few exploit long-time series of polarized synthetic aperture radar (SAR) imagery. To address this gap, we assessed the performance of COSMO-SkyMed <italic>X</italic>-band dual-polarized (HH, VV) data in a test area in Ponte a Elsa (central Italy) in January–September 2020 and 2021. A deep learning convolutional neural network (CNN) classifier arranged with two different architectures (1-D and 3-D) was trained and used to recognize ten classes. Validation was undertaken with <italic>in situ</italic> measurements from regular field campaigns carried out during satellite overpasses over more than 100 plots each year. The 3-D classifier structure and the combination of HH+VV backscatter provide the best classification accuracy, especially during the first months of each year, i.e., 80% already in April 2020 and in May 2021. Overall accuracy above 90% is always marked from June using the 3-D classifier with HH, VV, and HH+VV backscatter. These experiments showcase the value of the developed SAR-based early-season crop mapping approach. The influence of vegetation phenology, structure, density, biomass, and turgor on the CNN classifier using <italic>X</italic>-band data requires further investigations, along with the relatively low producer accuracy marked by vineyard and uncultivated fields.
High-redshift primordial galaxies have recently been found with evolved stellar populations and complex star-formation histories reaching back to 250 Myr after the Big Bang. Their intense bursts of star-formation appear to be interspersed with sustained periods of strong quenching, however the processes underlying this evolutionary behaviour remain unclear. Unlike later epochs, galaxies in the early Universe are not located in large associations like clusters. Instead, they co-evolve with their developing circumgalactic halo as relatively isolated ecosystems. Thus, the mechanisms that could bring about the downfall of their star-formation are presumably intrinsic, and feedback processes associated with their intense starburst episodes likely play an important role. Cosmic rays are a viable agent to deliver this feedback, and could account for the star-formation histories inferred for these systems. The cosmic ray impact on galaxies may be investigated using the wealth of multi-wavelength data soon to be obtained with the armada of new and upcoming facilities. Complementary approaches to probe their action across the electromagnetic spectrum can be arranged into a distance ladder of cosmic ray feedback signatures. With a clear understanding of how cosmic ray activity in primordial systems can be traced, it will be possible to extend this ladder to high redshifts and map-out the role played by cosmic rays in shaping galaxy evolution over cosmic time.
The history of the Universe and the forces that shaped it are encoded in maps of the cosmos. From understanding these maps, we gain insights into nature that are inaccessible by other means. Unfortunately, the connection between fundamental physics and cosmic observables is often left to experts (and/or computers), making the general lessons from data obscure to many particle theorists. Fortunately, the same basic principles that govern the interactions of particles, like locality and causality, also control the evolution of the Universe as a whole and the manifestation of new physics in data. By focusing on these principles, we can understand more intuitively how the next generation of cosmic surveys will inform our understanding of fundamental physics. In these lectures, we will explore this relationship between theory and data through three examples: light relics ($N_{\rm eff}$) and the cosmic microwave background (CMB), neutrino mass and gravitational lensing of the CMB, and primordial non-Gaussianity and the distribution of galaxies. We will discuss both the theoretical underpinnings of these signals and the real-world obstacles to making the measurements.