Light Higgsinos below several hundred GeV are favored or required by the naturalness of low-energy supersymmetry. If only Higgsinos are light while other sparticles are sufficiently heavy, we have the so-called light Higgsino scenario. Confronted with the muon $g-2$ data, this scenario is examined in this work. Since in this scenario the lightest sparticle is Higgsino-like, we need to also consider the dark matter constraints. Assuming a light Higgsino mass parameter $\mu$ in the range of 100–400 GeV while gaugino mass parameters above TeV, we explore the parameter space under the muon $g-2$ data and the dark matter constraints. We find that, to explain the muon $g-2$ anomaly at $2\sigma$, the winos and sleptons are, respectively, upper bounded by 3 TeV and 800 GeV. In this case, we find that the light Higgsino-like dark matter can sizably scatter with nucleon and thus the allowed parameter space can be covered almost fully by the future LZ dark matter detection project. We also perform a Monte Carlo simulation to figure out the potential of High-Luminosity Large Hadron Collider (HL-LHC) to detect the light sleptons in this scenario. It turns out that compared with the current LHC limits, the HL-LHC can further cover a part of the parameter space.

We estimate the sensitivity of the DUNE experiment to new physics particles interacting with neutrinos, considering the dipole portal to heavy neutral leptons and a neutrinophilic scalar with lepton-number 2 as examples. We demonstrate that neutrinos from the high-energy tail of the DUNE flux, with energies $E_{\nu }\gtrsim 5–10\mathrm{GeV}$, may significantly improve the sensitivity to these models, allowing to search for particles as heavy as $\simeq 10\mathrm{GeV}$. We also study the impact of the so-called tau-optimized neutrino beam configuration, which slightly improves sensitivity to the new physics models considered here. For both models, we consider new production channels (such as deep-inelastic scattering) and provide a detailed comparison of different signatures in the detector.

In this paper, we work with 16 different single scalar particle extensions of the Standard Model. We present the sets of dimension-six effective operators and the associated Wilson coefficients as functions of model parameters after integrating out the heavy scalars up to one loop, including the heavy-light mixing, for each such scenario. Using the correspondence between the effective operators and the observables at the electroweak scale, and employing Bayesian statistics, we compute the allowed ranges of new physics parameters that are further translated and depicted in two-dimensional Wilson coefficient space in light of the latest CMS and ATLAS data up to 137 and $139{\mathrm{fb}}^{-1}$, respectively. We also adjudge the status of those new physics extensions that offer similar sets of relevant effective operators. In addition, we provide a model-independent fit of 23 Standard Model effective field theory Wilson coefficients using electroweak precision observables, single- and di-Higgs data, as well as kinematic distributions of diboson production.

We prove that ideal chiral hydrodynamics, as derived from chiral kinetic theory, is acausal and its initial-value problem is ill posed, both in the linearized case around a local equilibrium solution and also in the full nonlinear regime. Therefore, such theory cannot be used to determine how the chiral anomaly affects the hydrodynamic evolution. We show that these fundamental issues can be fixed by using different definitions (frames) for the hydrodynamic fields. This leads to a causal theory of ideal chiral hydrodynamics where the vorticity strength is constrained by the coefficient that encodes the anomaly.

This paper tests how effectively the bound states of strongly-interacting gauge theories are amenable to an emergent description as a thermal ensemble. This description can be derived from a conjectured minimum free-energy principle, with the entanglement entropy of two-parton subsystems playing the role of thermodynamic entropy. This allows us to calculate the ground-state hadron spectrum and wave function over a wide range of parton masses without solving the Schrödinger equation. We carry out this analysis for certain illustrative models in ($1+1$) dimensions and discuss prospects for higher dimensions.

We study relativistic corrections to the exclusive decay of $J/\psi$ into proton-antiproton final state. We calculate the relativistic QCD corrections to the dominant decay amplitude, which depend on the nucleon twist-3 light-cone distribution amplitudes only. It is shown that in this case the collinear factorization is also valid beyond the leading-order approximation. Our numerical estimates show that relativistic correction of relative order $v^2$ provides a large numerical impact.

When applied to the nonlinear matter distribution of the universe, neural networks have been shown to be very statistically sensitive probes of cosmological parameters, such as the linear perturbation amplitude ${\sigma }_8$. However, when used as a “black box,” neural networks are not robust to baryonic uncertainty. We propose a robust architecture for constraining primordial non-Gaussianity $f_{NL}$, by training a neural network to locally estimate ${\sigma }_8$, and correlating these local estimates with the large-scale density field. We apply our method to $N$-body simulations, and show that $\sigma (f_{NL})$ is 3.5 times better than the constraint obtained from a standard halo-based approach. We show that our method has the same robustness property as large-scale halo bias: baryonic physics can change the normalization of the estimated $f_{NL}$, but cannot change whether $f_{NL}$ is detected.

We propose a unifying approach that starts from the perturbative construction of trivializing maps by Lüscher and then improves on it by learning. The resulting continuous normalizing flow model can be implemented using common tools of lattice field theory and requires several orders of magnitude fewer parameters than any existing machine learning approach. Specifically, our model can achieve competitive performance with as few as 14 parameters while existing deep-learning models have around 1 million parameters for $SU(3)$ Yang-Mills theory on a ${16}^2$ lattice. This has obvious consequences for training speed and interpretability. It also provides a plausible path for scaling machine-learning approaches toward realistic theories.

We study the conductivities and entanglement structures of two different holographic gapped systems at zero density in the presence of boundaries within $\mathrm{AdS}/\mathrm{BCFT}$ (anti-de Sitter/boundary conformal field theory). The first gapped system is described by the Einstein-scalar gravity, and the second one is the dual of AdS soliton geometry. We show that in both these two systems the bulk and boundary conductivities along the spatial direction of the boundary of BCFT are trivial. For the first system, when we increase the size of the subsystem the renormalized entanglement entropy is always non-negative and monotonically decreasing with discontinuous, continuous, or smooth behavior, depending on the effective tension of the brane. For the AdS soliton with a boundary, the renormalized entanglement entropy exhibits a discontinuous drop only when we increase the size of the subsystem.

Close to equilibrium, the kinetic coefficients of a thermodynamic system must satisfy a set of symmetry conditions, which follow from the Onsager-Casimir principle. Here, we show that, if a system of hydrodynamic equations is analyzed from the perspective of the Onsager-Casimir principle, then it is possible to impose very strong symmetry conditions also on the principal part of such equations (the part with highest derivatives). In particular, we find that, in the absence of macroscopic magnetic fields and spins, relativistic hydrodynamics should always be symmetric-hyperbolic, when linearized about equilibrium. We use these results to prove that Carter’s multifluid theory and the Israel-Stewart theory in the pressure frame are both symmetric-hyperbolic in the linear regime. Connections with the GENERIC formalism are also explored.

We show that, unlike vacuum general relativity, Einstein-scalar theories allow balanced static, neutral, asymptotically flat, double-black hole solutions, for scalar field models minimally coupled to gravity, with appropriate self-interactions. These are scalar hairy versions of the double-Schwarzschild (or Bach-Weyl) solution, but regular on and outside the two (topologically spherical) horizons. The balancing repulsive force is provided by the scalar field. An explicit illustration is presented, using a Weyl-type construction adapted to numerical solutions, requiring no partial linearization, or integrability structure, of the Einstein-scalar equations. Fixing the couplings of the model, the balanced configurations form a one-parameter family of solutions, labeled by the proper distance between the black holes.

We study false vacuum decay in a black hole (BH) spacetime with an angular momentum. Considering the false vacuum region described by a Kerr–de Sitter geometry, under the thin wall approximation, we can obtain the stationary configuration of the vacuum bubble seen from the outside false vacuum region without specifying the geometry inside the domain wall. Then, assuming the true vacuum region is described by a Kerr geometry, we can fix the mass and the spin parameter for the Kerr geometry by imposing the first junction conditions and conservation of the angular momentum. Although the assumption of the Kerr geometry inside the domain wall cannot be fully consistent with the second junction conditions, we can roughly evaluate the error associated with this inconsistency by calculating the Brown-York quasilocal energy on the domain wall. Then the decay rate can be estimated by using the obtained parameters for the inside Kerr geometry and the Brown-York quasilocal energy. Our results support the statement that the BH spin suppresses the false vacuum decay in a BH spacetime.

We use the open source, community-driven, numerical relativity software, the einstein toolkit to study the physics of eccentric, spinning, nonprecessing binary black hole mergers with mass-ratios $q=\{2,4,6\}$, individual dimensionless spin parameters ${\chi }_{1z}=\pm 0.6$, ${\chi }_{2z}=\pm 0.3$, that include higher order gravitational wave modes $\ell \le 4$, except for memory modes. Assuming stellar mass binary black hole mergers that may be detectable by the advanced LIGO detectors, we find that including modes up to $\ell =4$ increases the signal-to-noise of compact binaries between 3.5% to 35%, compared to signals that only include the $\ell =|m|=2$ mode. We use two waveform models, TEOBResumS and SEOBNRE, which incorporate spin and eccentricity corrections in the waveform dynamics, to quantify the orbital eccentricity of our numerical relativity catalog in a gauge-invariant manner through fitting factor calculations. Our findings indicate that the inclusion of higher order wave modes has a measurable effect in the recovery of moderately and highly eccentric black hole mergers, and thus it is essential to develop waveform models and signal processing tools that accurately describe the physics of these astrophysical sources.

Superconducting cosmic strings can exhibit longitudinal, pinching instabilities in some regions of the parameter space. We make predictions about the onset of this instability using the thin string approximation (TSA) and develop an improved analysis that remains applicable for small wavelength perturbations, where the TSA breaks down. We use simulations of perturbed strings to assess the accuracy of the TSA, test the predictions of our new analysis and demonstrate an improvement over previous methods in the literature. Notably, it appears that the instabilities are typically present for a larger range of magnetic strings than previously expected, and we show examples of pinching instabilities also occurring in electric strings. However, both our simulations and predictions agree that strings near the chiral limit are free from pinching instabilities and in particular our results support our previously published claim that vortons can be stable to all classical perturbations if they are sufficiently large.

We investigate the decay rate of a false vacuum state in de Sitter space at high Hubble rates, using two methods: the Hawking-Moss instanton method which is fully quantum mechanical but relies on the saddle-point approximation, and the Starobinsky-Yokoyama stochastic approach which is nonperturbative but does not include quantum effects. We use the flux over population method to compute the Hawking-Moss decay rate at one-loop order, and demonstrate that in its domain of validity, it is reproduced by the stochastic calculation using the one-loop constraint effective potential. This suggests that the stochastic approach together with the constraint effective potential can be used to accurately describe vacuum decay beyond the saddle-point approximation.

We investigate impacts of long-wavelength gravitational waves (GWs) on nonlinear structure formation by utilizing the tidal separate universe simulations. Based on the equivalence of a long-wavelength GW to a uniform tidal field in a local frame, we provide a way to incorporate a long-wavelength GW into the tidal separate universe simulation as an effective anisotropic expansion. This methodology enables us to study effects of GWs on large-scale structure efficiently. We measure the anisotropic imprint in the local power spectrum from the tidal separate universe simulations with GWs, which corresponds to the scalar-scalar-tensor bispectrum in squeezed limit or the so-called power spectrum response to GWs. We also detect the halo tidal bias induced by GWs from the response of the halo-matter cross-power spectrum to GWs, as well as the linear shape bias (or the linear alignment coefficient) induced by GWs from the one-point function of the halo ellipticity. In contrast to the case of the tidal field induced by scalar perturbations, we discover that the wave number dependence of the temporal evolution of GWs naturally causes these biases to be scale-dependent. We also find that this scale dependence is well approximated by the second-order density induced by the coupling between scalar and tensor perturbation. This highlights that the structure formation, especially the process to determine the halo shape, is nonlocal in time. Our findings lay the foundation for predicting the impact of GWs on large-scale structure.

We baseline with current cosmological observations to forecast the power of the Dark Energy Spectroscopic Instrument (DESI) in two ways: (1) the gain in constraining power of parameter combinations in the standard $\mathrm{\Lambda }\mathrm{CDM}$ model, and (2) the reconstruction of quintessence models of dark energy. For the former task we use a recently developed formalism to extract the leading parameter combinations constrained by different combinations of cosmological survey data. For the latter, we perform a nonparametric reconstruction of quintessence using the effective field theory of dark energy. Using mock DESI observations of the Hubble parameter, angular diameter distance, and growth rate, we find that DESI will provide significant improvements over current datasets on $\mathrm{\Lambda }\mathrm{CDM}$ and quintessence constraints. Including DESI mocks in our $\mathrm{\Lambda }\mathrm{CDM}$ analysis improves constraints on ${\mathrm{\Omega }}_m$, $H_0$, and ${\sigma }_8$ by a factor of two, where the improvement results almost entirely from the angular diameter distance and growth of structure measurements. Our quintessence reconstruction suggests that DESI will considerably improve constraints on a range of quintessence properties, such as the reconstructed potential, scalar field excursion, and the dark energy equation of state. The angular diameter distance measurements are particularly constraining in the presence of a non-$\mathrm{\Lambda }\mathrm{CDM}$ signal in which the potential cannot be accounted for by shifts in $H_0$ and ${\mathrm{\Omega }}_m$.

We compute the hybrid star (HS) properties with the help of Maxwell construction. For the purpose we choose a fixed hadronic model and four different forms of MIT bag model for the quark phase. We investigate thoroughly the effects of the different parameters of the bag model on the speed of sound in HS matter and the structural properties of HSs in the light of the various recent constraints on them from astrophysical observations. We also examine the importance of each parameter involved in these four forms of bag model in the context appearance of special points (SPs) in the mass-radius ($M-R$) variation of HSs. We find that among all these parameters the bag pressure play the most significant role in the emergence of the SPs in the $M-R$ dependence of HSs.

As engineered systems grow in complexity, there is an increasing need for automatic methods that can detect, diagnose, and even correct transient anomalies that inevitably arise and can be difficult or impossible to diagnose and fix manually. Among the most sensitive and complex systems of our civilization are the detectors that search for incredibly small variations in distance caused by gravitational waves—phenomena originally predicted by Albert Einstein to emerge and propagate through the universe as the result of collisions between black holes and other massive objects in deep space. The extreme complexity and precision of such detectors causes them to be subject to transient noise issues that can significantly limit their sensitivity and effectiveness. They are also subject to nearly constant development, improvement, commissioning and other invasive actions that change the nature of the data and its artifact contamination. In this work, we present a demonstration of a method that can detect and characterize emergent transient anomalies of such massively complex systems. We illustrate the performance, precision, and adaptability of the automated solution via one of the prevalent issues limiting gravitational-wave discoveries: noise artifacts of terrestrial origin that contaminate gravitational wave observatories’ highly sensitive measurements and can obscure or even mimic the faint astrophysical signals for which they are listening. Specifically, we demonstrate how a highly interpretable convolutional classifier can automatically learn to detect transient anomalies from auxiliary detector data without needing to observe the anomalies themselves. We also illustrate several other useful features of the model, including how it performs automatic variable selection to reduce tens of thousands of auxiliary data channels to only a few relevant ones; how it identifies behavioral signatures predictive of anomalies in those channels; and how it can be used to investigate individual anomalies and the channels associated with them. The solution outlined is broadly applicable, enabling automated anomaly discovery and characterization and human-in-the-loop anomaly elimination.