论文

Distinguishability is a central concept in information theory and extends naturally to quantum systems. This work shows that, for any two finite-dimensional memoryless quantum channels, parallel, adaptive and general testing strategies achieve the same Stein exponent at every fixed type-I error tolerance $ε\in(0,1)$, namely the regularized channel relative entropy. When this rate is finite, any larger type-II exponent forces the probability of correctly accepting the null hypothesis to decay exponentially. Thus, adaptivity provides no asymptotic advantage. The key step is proving the continuity of the regularized sandwiched Rényi channel divergence at order one. We also derive the exact strong-converse exponent for general testers.

The properties and behavior of strongly interacting matter at extreme densities can not only be determined through terrestrial experiments or through theoretical considerations, but also astrophysical observations of neutron stars (NSs) and binary neutron star systems become increasingly important to obtain complementary information. In light of these findings, we perform a Bayesian study inferring the NS equation of state (EoS) by incorporating constraints from the direct Urca (dUrca) process, thereby including information on matter composition in addition to traditionally used macroscopic observables. We implement a self-consistent treatment of $β$-equilibrium and charge neutrality in the \textsc{jester} framework, including the calculation of the proton fraction and the onset of nucleonic dUrca in the presence of electrons and muons. We combine constraints from chiral effective field theory, astrophysical measurements of NS masses, radii, and tidal deformabilities, and observations of rapidly and slowly cooling neutron stars. The dUrca constraint seems to be in favor of stiffer EoSs, but --at the current stage-- has only a minor impact on macroscopic NS properties once we include other nuclear and astrophysical constraints. In contrast, the dUrca information provides a constraint on the composition of canonical-mass NSs favoring a higher proton fraction inside the star, illustrating the complementary information carried by cooling observations. Our results demonstrate the potential of incorporating composition-sensitive observables into multimessenger inference and provide a step toward a more comprehensive treatment of dUrca constraints with microscopically motivated EoS models.

Exclusive photoproduction is an important probe of nuclear parton distributions at low Bjorken-$x$. The Good-Walker paradigm relates coherent photoproduction to the average nuclear configuration, giving access to the transverse distribution of gluons in a target, while incoherent photoproduction is sensitive to fluctuations such as gluonic hotspots. Efficiently separating coherent and incoherent interactions is a key challenge for experiments at the future Electron-Ion Collider (EIC). In this article, we study nuclear de-excitation via photon emission, and see how the finite photon detection efficiency leads to misidentification of incoherent emission. We compare the detection efficiency for incoherent $J/ψ$ production using the BeAGLE event generator for Ag-107, Au-197, and Pb-208 targets, for two different forward photon energy thresholds: 50 MeV and 200 MeV. The shell structures of the three species exhibit different incoherent tagging efficiencies due to differences in the lifetimes and energy levels of their excited states. Some of the low-lying states live long enough so that they decay outside the EIC detectors. Especially for the lower photon energy threshold, lead allows a higher tagging efficiency than gold, due to its lack of low-lying and/or long-lived excited states.

In string model building, flavor symmetries can arise from the geometric features of the compactification space. In the case of heterotic orbifold models, modular and traditional flavor symmetries can be related to both geometric and algebraic properties of the orbifold space group. Our goal is to study the origin of moduli-independent discrete flavor symmetries in symmetric heterotic orbifolds with non-Abelian point groups. We develop various methods based on the Abelianization and the geometric automorphisms of the orbifold space group to determine these symmetries and their associated charges for matter fields. Notably, our methods were applied to all 331 non-Abelian affine geometries, including roto-translations, suitable for delivering N=1 supersymmetric heterotic compactifications in four dimensions. This provides additional motivation to pursue the derivation of new types of phenomenologically viable models from string theory.

Could a collider become the symbol of everything that must be abandoned to save the climate? In the summer of 2026, this question ran through discussions within the Particles and Fields Division of the French Physical Society. An unacceptable carbon footprint, two EPR nuclear reactors, five hundred deaths, billions to be reallocated and, to top it all, unclear scientific objectives: the objections to CERN's Future Circular Collider (FCC) appeared to form an overwhelming indictment. This essay examines each charge in turn. Grounded in a clear and compelling scientific vision, it confronts emotionally charged imagery with orders of magnitude, distinguishes a project's footprint from its full balance sheet, considers the costs of postponing or abandoning it, and explores ways of reducing its impacts-including the still uncertain prospect of natural hydrogen. The climate alone does not decide the future of the FCC; it requires us to judge the available choices by their real consequences. Developed for the public debate organised by France's National Commission for Public Debate and for the Swiss consultation, this essay is intended for the broadest possible readership, well beyond particle physics and the scientific community. It frames the FCC debate as a choice about the kind of society we want to build: should we organise society around renunciation and ever-shrinking horizons, or transform how we produce and choose a future worth wanting?

A new proposal called DM-SMC (Diffusion Model - Sequential Monte Carlo) is investigated, which samples ensembles defined in terms of an action, using diffusion models trained on samples from the ensemble. The SMC setup allows for accurate sampling in spite of an approximate diffusion model and the finite stepsize used in the numerical solution of the stochastic process. Improved update strategies are also investigated. Results are presented for a $Z_2$ symmetric scalar field theory in 2 dimensions near its 2nd order phase transition.

The LUX-ZEPLIN (LZ) experiment has reported an event consistent with a $248$ keV nuclear recoil. Explaining the absence of lower-energy recoil events typically calls for some form of upscattering that kinematically forbids such events. In this work, we present a framework in which the LZ observation has a neutrino origin, with atmospheric neutrinos providing the dominant flux in the required energy range. A scenario in which atmospheric neutrinos upscatter to a heavier neutral state would also produce a large number of neutral-current events in neutrino experiments. In particular, scattering on lighter nuclear targets results in much larger nuclear recoil energies compared to xenon, yet no such excess has been observed. We show that this constraint from neutrino experiments can be evaded if atmospheric neutrinos within a narrow energy window first produce a nearly monoenergetic state $N_1$, followed by the upscattering of $N_1$ to its heavier partner $N_2$ in LZ. In such a scenario, scattering on xenon becomes kinematically allowed for $N_2$ masses around $250$ MeV, while scattering on oxygen, carbon, and other targets used in large-scale neutrino experiments remains kinematically forbidden. We show that this two-step process, $ν\to N_1 \to N_2$, can be realized through a parametric resonance induced by a dark matter background that efficiently produces $N_1$, followed by $N_1 \to N_2$ upscattering mediated by a vector boson in a model with gauged $U(1)_B$. The latter interaction can be sufficiently stronger than the weak interaction, which is necessary to lift the neutrino floor and yield $\mathscr{O}(1)$ event at LZ.

Spontaneous scalarization of charged black holes in asymptotically flat spacetime has attracted much recent interest. It is recently reported that inside these spontaneously scalarized black holes, the Kasner parameter $β$ at the terminal singularity diverges as $β\propto(q/q_c-1)^{-γ}$ near the critical charge-to-mass ratio $q_c$, with an exponent $γ=1/2$ that appeared model independent within a wide class of couplings. In this paper we report a family of new universality classes in which $γ$ differs from 1/2. We show that all these critical behaviors are governed by the same emergent scaling symmetry at the would-be Cauchy horizon of the background Reissner-Nordström solution. This symmetry leads to a ``seesaw amplification'' to amplify exterior small scalar and produces a limiting autonomous system that is independent of the details of the theory. Our mechanism provides a unified picture of exterior scalarization and interior criticality and makes sharp numerical predictions that we test.

We introduce projected amorphous topological insulators (PATIs) that despite containing only a fraction ($x$) of otherwise randomly selected {\it disconnected} sites of a parent crystal, feature a quantized global topological invariant ({\it strong} PATIs) when its effective Hamiltonian is constructed by integrating out the residual sites of the original lattice. Within the topological regime of the parent model, additionally, there exists a critical $x$ below which such systems foster a {\it fragile} PATI that only supports quantized local topological marker on a small fraction of sites therein. Both strong and fragile PATIs accommodate in-gap modes near the boundary. The system also hosts a normal insulator in the entire trivial parameter regime of the lattice-based model for any $x$, devoid of gapless boundary modes, for which both global topological invariant and local topological marker vanish. We demonstrate these {\it possibly} generic outcomes by starting with a parent square lattice-based model for time-reversal symmetry breaking insulators. Then the strong-to-fragile PATI quantum phase transition, tunable via $x$, is characterized by the {\it mean} correlation length exponent $ν\in (1.00,1.46)$.

We describe a probabilistic approach to gravitational clustering. Working purely in configuration space, we show that the two-point function can be formulated in terms of a transition probability describing the likely final position of a particle given its initial position. The transition probability is initially sharply peaked and then over time broadens out in a diffusion-like manner. The effect is more pronounced for widely-separated particles (e.g.\ at the baryon acoustic scale), leading to an effective suppression of the two-point function in what is normally referred to as infrared resummation.

This paper investigates the numerical resolution of the Beurling-LASSO (BLASSO), a convex optimization framework that promotes sparsity in the space of measures. We consider its application to the estimation of Gaussian mixture models (GMMs) with an unknown number of components and unknown diagonal covariance matrices. Our approach combines the Conic Particle Gradient Descent (CPGD) principle with Riemannian gradient descent, to account for the underlying Fisher-Rao geometry of Gaussian distributions. Our contributions are twofold. First, we provide theoretical guarantees for the convergence of our algorithm. In particular, we establish exponential local convergence under a non-degeneracy condition on the solution and relate this assumption to a separation condition on the underlying statistical target. Second, we address practical implementation aspects of CPGD and present numerical experiments illustrating its performance. On the test cases considered, these experiments suggest that CPGD is more robust to overspecification of the number of components than the EM algorithm. We also investigate the impact of component separation on recovery accuracy.

Verified income is often unavailable in digital loan applications, forcing lenders to rely on reported income and potentially leading to over-lending, overly conservative offers, or rejection of creditworthy applicants. Cross-institutional data-sharing constraints make this problem especially difficult for smaller lenders with limited training data. We introduce FedIncome, a federated learning framework for income estimation that enables institutions to train a shared model without pooling raw borrower records. Using more than one million LendingClub loans partitioned into $50$ state-level clients, we simulate a heterogeneous lending consortium. The best federated model achieves out-of-time $R^2=0.608$, compared with $0.619$ for a pooled centralised benchmark. Small-sample clients obtain an average out-of-time $R^2$ improvement of $3.8$ percentage points relative to the pooled centralised benchmark, while the fitted client-level relationship places the empirical crossover at approximately $4,790$ training observations in this setting. When pooling is infeasible and the relevant alternative is local-only training, federation improves out-of-time performance across all sample-size groups, with the largest gains for data-scarce clients. We also combine federated income estimates with state- and income-specific debt-to-income thresholds. In a retrospective decision analysis, replacing reported income with the federated estimate increases simulated approval rates with only modest changes in observed default rates. FedIncome supports collaborative learning under data-locality constraints with little aggregate loss relative to pooled training and larger gains relative to local-only estimation.