Recently, the size-dependence of high-order harmonic generation (HHG) in quantum dots has been investigated experimentally. In particular, for longer driving wavelengths and QDs smaller than 3\,nm, HHG was strongly suppressed, however, there is no computational model capable of describing the strong-field response of such systems. In this work, we introduce a computationally efficient three-dimensional real-space tight-binding model specifically designed for the simulation of HHG in confined systems. The model parameters are meticulously derived from density functional theory (DFT) calculations for the semiconductor bulk, followed by a process of Wannierization. Our findings demonstrate that the proposed model accurately captures the observed dependency of the HHG yield on the quantum dot size. Additionally, we simulate the HHG yield for elliptically polarized pulses for different QD-sizes and driving wavelengths up to $5\,μ{\mathrm{m}}$. The herein proposed model fills the theoretical void in simulating HHG within medium-sized nanostructures, which cannot be described by methods applied for periodic solids or small molecules or atoms.

Soft X-ray angle resolved photoemission spectroscopy (SX-ARPES) is one of the most powerful spectroscopic techniques to visualize the three-dimensional bulk electronic structure in reciprocal lattice space. Compared with ARPES employing low-energy photon sources, the time burden imposed by a lower photoelectron yield, stemming from the photoionization cross-section, has been a persistent technical challenge. To address this challenge, we have developed a noise removal system by using the deep prior-based method and integrated it into the micro focused SX-ARPES (μSX-ARPES) system at BL25SU in SPring-8. Our implemented system effectively eliminates the grid and spike noise typically present in ARPES data acquired using the voltage Fixed-mode, within about 30 seconds. We demonstrate, through the μSX-ARPES measurements on a single crystal of CeRu2Si2, that data with sufficient statistical accuracy can be obtained in approximately 40 seconds. In addition, we present the potential of high signal-to-noise ratio ARPES measurement, achieving an energy resolution of 51.6 meV at an excitation energy of 708 eV in μSX-ARPES measurements on polycrystalline gold. Our developed system successfully reduces the time burden in SX-ARPES and paves the way for advancements in lower photoelectron yield measurements, such as those requiring higher energy resolution and three-dimensional nonequilibrium measurements.

We classify the irreducible anyon sectors of Levin-Wen models over an arbitrary unitary fusion category $\mathcal{C}$, showing that they are in one-to-one correspondence with equivalence classes of simple objects of the Drinfeld center $Z(\mathcal{C})$. We achieve this by making explicit how the Levin-Wen Hamiltonian stabilizes subspaces isomorphic to state spaces of the corresponding Turaev-Viro TQFT, and developing a detailed understanding of these state spaces on punctured disks. In particular, we construct Drinfeld insertion operators on such spaces which can move anyons between the punctures, and can change their fusion channels. Using these Drinfeld insertions, we construct explicit string operators that excite anyons above the ground state. The fusion and braiding properties of these anyons will be analysed in a companion paper.

Fluid mixtures, such as the cellular cytoplasm and synthetic DNA nanostars, can spontaneously compartmentalize into many coexisting phases through liquid-liquid phase separation. Despite the diversity of fluid structures that emerge from interactions between different phases, the physical principles governing their spatiotemporal organization remain unclear. In this work, we show that the dynamics of multicomponent phase separation are intimately connected to mathematical coloring problems, including the four-color theorem. By confining the system to thin geometries, we demonstrate that the four-color theorem permits arrangements of fluid compartments that lead to suppressed coalescence. As a consequence, hydrodynamics is arrested, and the diffusion-dominated coarsening dynamics can be collapsed to a universal master curve. Varying the fluid interfacial tensions can change which arrangements are energetically permissible, resulting in highly complex coarsening dynamics that differ for each phase. In unconfined three-dimensional systems, the absence of an equivalent to the four-color theorem means that suppression of coalescence is only reached asymptotically for large numbers of phases, rather than at a sharp threshold. In general, the coloring approach employed here offers a topological framework for understanding the dynamic behaviour of phase separating fluid mixtures.

As is known, every finite-dimensional algebra over a field is isomorphic to the centralizer algebra of \textbf{two} matrices. So it is fundamental to study first the centralizer algebra of a single matrix, called a centralizer matrix algebra. In this article, stable equivalences between centralizer matrix algebras over arbitrary fields are completely characterized in terms of a new type of equivalence relation on matrices. Moreover, stable equivalences of centralizer matrix algebras over any fields induce stable equivalences of Morita type, thus preserve dominant, finitistic and global dimensions. Our methods also show that the Alperin--Auslander/Auslander--Reiten conjecture holds true for stable equivalences between an arbitrary algebra and a centralizer matrix algebra over a common field.

We study null geodesics that connect the two asymptotically flat regions of the maximally extended Kerr spacetime. These vortical geodesics traverse both horizons and pass through the ring singularity, linking the positive-$r$ exterior to the negative-$r$ asymptotic side. Using impact parameters, we identify a closed subset of parameter space, the inner throat, where the radial potential has no real roots, and photons exhibit no radial turning points. In this region, at most two constant-latitude geodesics exist, one of which is aligned with the principal null direction. We also identify the forbidden polar-angle band that limits the range of geodesics reaching an asymptotic observer. We solve the geodesic equations analytically and numerically in Eddington-Finkelstein-like coordinates, obtaining mutually consistent results that correct and extend previously available formulae. The resulting trajectories are used to construct simulated views for an observer in the negative-$r$ domain, revealing strong image distortion and inversion, with possible implications for analogous white-hole configurations.

We extend the Harrow-Hassidim-Lloyd (HHL) algorithm, which is well-studied in the qubit framework, to its qutrit counterpart (which we call qutrit HHL, as opposed to qubit HHL, which is HHL using qubits), and develop a program for its implementation. We design Weyl-Heisenberg gadgets, the qutrit equivalents of Pauli gadgets, and come up with a practical implementation scheme for qutrit HHL. We test HHL with qutrits for simple matrices and verify the results against the expected outcomes. We apply the algorithm to quantum chemistry, and in particular, to the potential energy curve calculations of the model problem of the Hydrogen molecule in the split valence basis. We do so for two cases: 1-qutrit and 2-qutrit input states, where the latter makes use of our gadgets. We compare the number of qudits and the number of gates required between qubit and qutrit HHL implementations. In general, we find that for a fixed precision, the qutrit HHL circuit requires fewer number of qudits and comparable number of two-qudit gates than its qubit counterpart.

We demonstrate channel-selective frequency up-conversion from telecom wavelengths around 1540 nm for optical fiber communication to visible wavelengths around 780 nm, based on second-order optical nonlinearity in a cavity of the converted modes. In our experiment, we selectively convert a light from any frequency mode within frequency-multiplexed telecom signals to a desired output mode, determined by the cavity resonances. Based on the experimental results of the frequency up-conversion, we derive the signal-to-noise ratio of the process at the single-photon level, and discuss its applicability to channel-selective quantum frequency conversion (CS-QFC) in the context of frequency-multiplexed quantum networks. Finally, we describe specific use cases of the CS-QFC, which show its utility as a reconfigurable switching element in frequency-multiplexed networks, particularly for selectively performing Bell-state measurements between two photons originating from different frequencies.

In the single-field case, Horndeski provides the most general scalar-tensor theory with second-order field equations. By contrast, systematic multi-field extensions remain incomplete: while the general field equations for the bi-Horndeski case are known, a general action has not been established, and for cases with three or more fields, neither a general action nor general equations are available. We characterize Horndeski by two mild axioms: closure under invertible pure disformal transformations and the requirement that the theory includes the minimal Horndeski theory. Under this characterization, we recover the standard single-field action up to boundary terms and obtain a practical path to multi-field constructions. In particular, we show that antisymmetric structures, such as those identified by Allys, Akama, and Kobayashi, appear within this framework, and indicate that this viewpoint has the potential to account for features captured by known bi-Horndeski equations.

Collisionless shocks in space and astrophysical plasmas mediate energy exchange between charged particles and fields in two or more plasma flows. In this study we analyze the evolution of ion distributions around a reformation cycle of a quasi-parallel shock. We use multi-point in-situ observations in the foreshock region of the Earths bow shock of a transient foreshock structure as it generates a shock. We find that backstreaming ions in the foreshock create a density and magnetic field depletion known as caviton which locally changes the shock geometry. Gyrating suprathermal ions that emerge within the caviton and reach the upstream edge of the core create a cross-field current imbalance that results in the nonlinear growth of a new shock layer. The new shock forms from the background foreshock fields over a distance of ~6 ion inertial lengths ($l_i$) and within 4.5 to 11.2 $l_i$ from the main bow shock. We find that plasma compression at the new thin shock layer is due to compactification of the cold upstream ion beam by high amplitude magnetic field-aligned electrostatic fields. At later stages, the plasma compression expands to form a new sheath.

BL Lac has entered an active state since 2020, with multiwavelength observations revealing intense flares. In this study, we conducted 12-night multicolor optical monitoring using an 85 cm telescope from 2020 September to 2024 June and collected long-term broad-band archived data from radio to $γ$-rays. Intraday variabilities were detected on four nights, and most of them exhibited a bluer-when-brighter behavior. Both clockwise and counterclockwise spectral hysteresis loops were found within a single night. However, no reliable intraband time lag was detected for the intranight variabilities. On long timescales, the cross-correlation analysis shows that the variations of the optical, X-ray, and $γ$-ray bands do not reveal an obvious time delay, while the variations in the radio bands lagged them by about 370 days. The measured time lags suggest two distinct emission regions respectively responsible for the optical to $γ$-ray radiation and for the radio radiation, with a spatial separation of approximately $4.50\times10^{19}\ \rm cm$. We modeled the broad-band spectral energy distributions during four flaring epochs and one quiescent epoch, and found evidence for the possible persistent existence of a very high energy emission region. We also confirmed a spectral evolution of the source from an intermediate synchrotron peaked BL Lac object to a low synchrotron peaked BL Lac object.

Open quantum systems exhibit dynamics ranging from unitary evolution to irreversible dissipation. While the Gorini--Kossakowski--Sudarshan--Lindblad (GKSL) equation uniquely characterizes Markovian CPTP evolution, many physical platforms display non-Markovian features such as algebraic relaxation and coherence backflow. Fractional calculus provides a natural way to model such long-memory behavior through power-law temporal kernels introduced by fractional time derivatives. Here we develop a unified framework that embeds fractional master equations within the broader hierarchy of open-system formalisms. The fractional equation forms a structured subclass of memory-kernel models, reduces to the Lindblad form at unit order, and, through Bochner--Phillips subordination, admits a CPTP representation as an average over Lindblad semigroups. Its resolvent structure further connects fractional dynamics to established non-Markovian approaches, including Nakajima--Zwanzig kernels and hierarchical equations of motion, providing a compact surrogate for long-memory effects. This formulation positions fractional calculus as a rigorous and practical language for quantum dynamics with intrinsic memory, supporting both analytical insight and efficient quantum simulation.

Forensic DNA databases in the United States have expanded substantially over the past two decades. However, comprehensive, harmonized data describing database structure and composition remain limited. This dataset series documents forensic DNA infrastructure across national and state levels from 2001 to 2025. It includes a reconstructed time series of monthly National DNA Index System (NDIS) statistics from FBI archives, capturing counts of offender, arrestee, and forensic profiles, participating laboratory totals, and investigations aided. A complementary dataset compiles publicly available state-level statistics and policy metadata on arrestee collection laws, familial search practices, and DNA collection statutes across all 50 states. A third dataset provides standardized demographic and annual collection data obtained through previously published public records requests, including sex and racial composition where reported. Together, these resources provide a foundation for studying the historical development of forensic DNA systems in the U.S., enabling longitudinal and cross-sectional analyses of database growth, policy variation, and reporting practices across jurisdictions.

The adsorption of volatile molecules onto dust grain surfaces fundamentally influences dust-related processes, including condensation of gas-phase molecules, dust coagulation, and planet formation in protoplanetary disks. Using advanced ab-initio density functional theory with r$^2$SCAN+rVV10 van der Waals functionals, we calculate adsorption energies of H$_2$, H$_2$O, and CO on carbonaceous (graphene, amorphous carbon) and silicate (MgSiO$_3$) surfaces. Results reveal fundamentally different adsorption mechanisms: weak physisorption on carbonaceous surfaces ($|Δε_{\rm ad}|\sim 0.1-0.2~{\rm eV}$) versus strong chemisorption on silicates ($|Δε_{\rm ad}|\sim 0.5-1.5~{\rm eV}$) via coordination bonds. Kinetic Monte Carlo simulations incorporating these energies demonstrate divergent surface evolution: carbonaceous grains exhibit distinct condensation radius compared to silicates, while the cocrystal of H$_2$O and CO significantly increases the desorption temperature of CO. The actual radii of gas-phase molecule depletion could thus be a comprehensive result of temperatures, chemical compositions, and even evolution tracks. Meanwhile, silicates maintain chemisorbed molecular coatings throughout most disk regions. Such dichotomy in surface coverage could also provide a natural mechanism for carbon depletion in inner planetary systems.

To validate key technologies for wide field-of-view (FOV) X-ray polarization measurements, the Cosmic X-ray Polarization Detector (CXPD) CubeSat series has been developed as a prototype platform for the Low-Energy X-ray Polarization Detector (LPD) onboard the POLAR-2 mission. The wide-FOV design significantly increases the complexity of the background environment, posing notable challenges for real-time gamma-ray burst (GRB) identification. In this work, we propose an in-orbit GRB identification method based on machine learning, using simulated spectral data as input. A training dataset was constructed using a Geant4-based simulator, incorporating in-orbit background and GRB events modeled within the 2-10 keV energy range. To meet the computational constraints of onboard processing, we employ a multimodal large language model (MLLM), which is fine-tuned using low-rank adaptation (LoRA) based on miniCPM-V2.6 and quantized to 4-bit precision. The model achieves perfect classification accuracy on validation data and demonstrates strong regression performance in estimating GRB spectral indices, with an RMSE of 0.118. Furthermore, we validate the feasibility of onboard deployment through a simulated satellite data processing pipeline, highlighting the potential of our approach to enable future real-time GRB detection and spectral analysis in orbit.

Combining a continuous "slab" density with discrete "spike" mass at zero, spike-and-slab priors provide important tools for inducing sparsity and carrying out variable selection in Bayesian models. However, the presence of discrete mass makes posterior inference challenging. "Sticky" extensions to piecewise-deterministic Markov process samplers have shown promising performance, where sampling from the spike is achieved by the process sticking there for an exponentially distributed duration. As it turns out, the sampler remains valid when the exponential sticking time is replaced with its expectation. We justify this by mapping the spike to a continuous density over a latent universe, allowing the sampler to be reinterpreted as traversing this universe while being stuck in the original space. This perspective opens up an array of possibilities to carry out posterior computation under spike-and-slab type priors. Notably, it enables us to construct sticky samplers using other dynamics-based paradigms such as Hamiltonian Monte Carlo; in fact, original sticky process can be established as a partial position-momentum refreshment limit of our Hamiltonian sticky sampler. Our theoretical and empirical findings suggest these alternatives to be at least as efficient as the original sticky approach.

We establish the integrability of a family of Sachdev-Ye-Kitaev (SYK) models with uniform $p$-body interactions. We derive the R-matrix and mutually commuting transfer matrices that generate the Hamiltonians of these models, and obtain their exact eigenspectra and eigenstates. Remarkably, the R-matrix is that of the critical transverse-field Ising chain. This work reveals an unexpected connection between the SYK model, central to many-body quantum chaos, and the critical Ising chain, a cornerstone of statistical mechanics.

Within the biological, physical, and social sciences, there are two broad quantitative traditions: statistical and mathematical modeling. Both traditions have the common pursuit of advancing our scientific knowledge, but these traditions have developed largely independently using distinct languages and inferential frameworks. This paper uses the notion of identification from causal inference, a field originating from the statistical modeling tradition, to develop a shared language. I first review foundational identification results for statistical models and then extend these ideas to mathematical models. Central to this framework is the use of bounds, ranges of plausible numerical values, to analyze both statistical and mathematical models. I discuss the implications of this perspective for the interpretation, comparison, and integration of different modeling approaches, and illustrate the framework with a simple pharmacodynamic model for hypertension. To conclude, I describe areas where the approach taken here should be extended in the future. By formalizing connections between statistical and mathematical modeling, this work contributes to a shared framework for quantitative science. My hope is that this work will advance interactions between these two traditions.

The adiabatic theorem is one of the most interesting and significant theorems in quantum mechanics. However, the adiabatic theorem can fail for general non-Hermitian quantum systems. In this paper, by utilizing the complex geometric phase, the functional calculus for biorthogonal systems and the Grönwall inequality, we prove rigorously that the adiabatic theorem is still valid for diagonalizable non-Hermitian systems with real eigenvalues. The proof also justifies the definition of a complex Berry phase in non-Hermitian systems.

Advanced space technology systems often face high fixed costs, can serve limited non-government demand, and are significantly driven by non-market motivations. While increased entrepreneurial activity and national ambitions in space have encouraged planners at public space agencies to develop markets around such systems, the very factors that make the recent growth of the space economy so remarkable also challenge planners' efforts to develop and sustain markets for space-related goods and services. I propose a graphical framework to visualize the number of competitors a market can sustain as a function of the industry's cost structure; the distribution of government support across direct purchases, direct investments, and shared infrastructure; and the magnitude of non-government demand. Building on public goods theory, the framework shows how marginal dollars invested in shared infrastructure can create non-rival benefits supporting more competitors per dollar than direct purchases or subsidies. I demonstrate the framework with a stylized application inspired by NASA's Commercial LEO Destinations program. Under cost and demand conditions consistent with public data, independent stations generate industry-wide losses of \$355 million annually, while shared core infrastructure enables industry-wide profits of \$154 million annually. I also outline key directions for future research on public investment and market development strategies for advanced technologies.

As quantum computing hardware continues to advance, the integration of such technology with quantum algorithms is anticipated to enable the decryption of ciphertexts produced by RSA and Elliptic Curve Cryptography (ECC) within polynomial time. In response to this emerging threat, the U.S. National Institute of Standards and Technology (NIST) finalized a series of Post-Quantum Cryptography (PQC) standards in August 2024 and outlined a roadmap for PQC migration. Consequently, the design of X.509 certificates that adhere to PQC standards has become a crucial focus in the development of certificate management systems. To further strengthen security and facilitate a smooth migration process, several hybrid certificate schemes have been proposed internationally based on the X.509 certificate format, including the composite scheme, the catalyst scheme, and the chameleon scheme. This study presents a comprehensive analysis and comparison of these hybrid certificate schemes from multiple perspectives (e.g., certificate size, computational efficiency, and migration feasibility) to assess their suitability for various applications and services.

We present the first next-to-leading-logarithmic QCD analysis of the electromagnetic corrections to the semileptonic weak Hamiltonian, including the mixed $\mathcal{O}(α\,α_s^2)$ corrections to the vector coupling $g_V$. The analysis combines the evaluation of three-loop anomalous dimensions and two-loop matching corrections with a consistent factorization of short-distance QCD effects. The latter is implemented through a scheme change based on a $d$-dimensional operator product expansion performed inside the loop integrals. The resulting renormalization-group--improved expression for the radiative correction $Δ^V_R = 2.436(16)\%$ can be systematically refined using input from lattice QCD and perturbation theory and improves the consistency of first-row CKM unitarity tests.

Self-supervised learning (SSL) has significantly advanced acoustic representation learning. However, most existing models are optimised for either speech or audio event understanding, resulting in a persistent gap between these two domains. We address this gap with SPEAR (SPEech and Audio Representations), a self-supervised framework that distils complementary knowledge from a speech-focused SSL teacher and a general-audio SSL teacher into a single unified model. SPEAR applies multi-codebook vector quantisation to continuous teacher representations to produce fine-grained discrete tokens that capture both semantic and acoustic information. To effectively integrate these heterogeneous representations, SPEAR jointly predicts them given a masked input with an asymmetric pre-training loss. We further improve robustness in complex sound scenes through a novel token mixing mechanism. Extensive experiments demonstrate that SPEAR consistently outperforms existing unified speech and audio models. SPEAR establishes a new state-of-the-art on the SUPERB benchmark, surpassing WavLM Large on 12 of 15 tasks, while achieving competitive performance on the HEAR benchmark. These results position SPEAR as a versatile foundation for general-purpose speech and audio representation learning. The code and pre-trained models will be released.

This is a follow-up of arXiv:2412.07470 [hep-th]. A simplified version of the SM plus gravity, put forward there, is presented here and some of its aspects delved into. The basic structure consists of two sectors, left and right, with chirally mirror fermions and scalars, as well as $SU(3)$ and $U(1)$ gauge fields, while the $SU(2)$ gauge fields as well as the metric are in common to both sectors. This structure is dictated by the request to cancel all dangerous anomalies. The left sector consists of the fermion, gauge and scalar fields of the SM, now minimally coupled to gravity. The right sector is a mirror image of the left, with distinct fields, except the metric and the $SU(2)$ gauge potentials. The first new aspect is the proposed and motivated interpretation of the right sector as the dark matter one. The second new subject covered here is Weyl symmetry and its possible application to cosmology and its theoretical fallout on unitarity and renormalization of the model. A background solution of the Weyl invariant theory is derived, which may apply to the very early stages of the universe. This solution also suggests interesting applications to the cosmological constant problem. On the quantum field theory side the subject of Weyl symmetry and Weyl anomalies is reviewed and, among other things, an application of the WZ terms is illustrated to the problem of one-loop quantization of the model which may avoid negative norm states.

Automatic differentiation provides an efficient means of computing derivatives of complex functions with machine precision, thereby enabling differentiable simulation. In this work, we propose the use of the norm of the tangent map, obtained from differentiable tracking of particle trajectories, as a computationally efficient indicator of chaotic behavior in phase space. In many cases, a one-turn or few-turn tangent map is sufficient for this purpose, significantly reducing the computational cost associated with dynamic aperture optimization. As an illustrative application, the proposed indicator is employed in the dynamic aperture optimization of an ALS-U lattice design.

In relation to Fuglede's conjecture, we establish several Plancherel-type identities and demonstrate the surjectivity of the Fourier transform between certain unbounded tiling sets of $\mathbb{R}$ that are in duality. In the terminology commonly used in the context of Fuglede's conjecture, our result states that an open set tiles $\mathbb{R}$ by the finite set $\{0,1,\dots,p-1\}$ if and only if it admits a spectrum (or, equivalently, a dual pair measure) given by the Lebesgue measure on $\left[-\tfrac{1}{2p}, \tfrac{1}{2p}\right] + \mathbb{Z}$.

As AI systems become increasingly capable and autonomous, domain experts' roles are shifting from performing tasks themselves to overseeing AI-generated outputs. Such oversight is critical, as undetected errors can have serious consequences or undermine the benefits of AI. Effective oversight, however, depends not only on detecting and correcting AI errors but also on the motivation and engagement of the oversight personnel and the meaningfulness they see in their work. Yet little is known about how domain experts approach and experience the oversight task and what should be considered to design effective and motivational interfaces that support human oversight. To address these questions, we conducted four co-design workshops with domain experts from psychology and computer science. We asked them to first oversee an AI-based grading system, and then discuss their experiences and needs during oversight. Finally, they collaboratively prototyped interfaces that could support them in their oversight task. Our thematic analysis revealed four key user requirements: understanding tasks and responsibilities, gaining insight into the AI's decision-making, contributing meaningfully to the process, and collaborating with peers and the AI. We integrated these empirical insights with the SMART model of work design to develop a generalizable framework of twelve design considerations. Our framework links interface characteristics and user requirements to the psychological processes underlying effective and satisfying work. Being grounded in work design theory, we expect these considerations to be applicable across domains and discuss how they extend existing guidelines for human-AI interaction and theoretical frameworks for effective human oversight by providing concrete guidance on the design of engaging and meaningful interfaces that support human oversight of AI systems.

How might messages about large language models (LLMs) found in public discourse influence the way people think about and interact with these models? To explore this question, we randomly assigned participants (N = 470) to watch short informational videos presenting LLMs as either machines, tools, or companions -- or to watch no video. We then assessed how strongly they believed LLMs to possess various mental capacities, such as the ability to have intentions or remember things. We found that participants who watched video messages presenting LLMs as companions reported believing that LLMs more fully possessed these capacities than did participants in other groups. In a follow-up study (N = 604), we replicated these findings and found nuanced effects on how these videos also impact people's reliance on LLM-generated responses when seeking out factual information. Together, these studies suggest that messages about LLMs -- beyond technical advances -- may shape what people believe about these systems and how they rely on LLM-generated responses.

Although the axion is the most compelling solution to the strong CP problem, the ad hoc introduced global Peccei-Quinn symmetry suffers from a severe fine-tuning problem known as the quality problem. In this Letter, we show that the discrete gauge symmetry $\mathbb Z_4 \times \mathbb Z_3$ motivated from the internal structure of the Standard Model can naturally predict a high-quality axion, leading to a distinct and testable parameter space. Remarkably, this minimal framework simultaneously accounts for neutrino masses, baryon asymmetry, and dark matter.

In this paper, we consider high-dimensional Lp-quantile regression which only requires a low order moment of the error and is also a natural generalization of the above methods and Lp-regression as well. The loss function of Lp-quantile regression circumvents the non-differentiability of the absolute loss function and the difficulty of the squares loss function requiring the finiteness of error's variance and thus promises excellent properties of Lp-quantile regression. Specifically, we first develop a new method called composite Lp-quantile regression(CLpQR). We study the oracle model selection theory based on CLpQR (call the estimator CLpQR-oracle) and show in some cases of p CLpQR-oracle behaves better than CQR-oracle (based on composite quantile regression) when error's variance is infinite. Moreover, CLpQR has high efficiency and can be sometimes arbitrarily more efficient than both CQR and the least squares regression. Second, we propose another new regression method,i.e. near quantile regression and prove the asymptotic normality of the estimator when p converges to 1 and the sample size infinity simultaneously. As its applications, a new thought of smoothing quantile objective functions and a new estimation are provided for the asymptotic covariance matrix of quantile regression. Third, we develop a unified efficient algorithm for fitting high-dimensional Lp-quantile regression by combining the cyclic coordinate descent and an augmented proximal gradient algorithm. Remarkably, the algorithm turns out to be a favourable alternative of the commonly used liner programming and interior point algorithm when fitting quantile regression.