The Heisenberg microscope provides a powerful mental image of the measurement process of quantum mechanics (QM), attempting to explain the uncertainty relation through an uncontrollable back-action from the measurement device. However, Heisenberg's proposed back-action uses features that are not present in the QM description of the world, and according to Bohr not present in the world. Therefore, Bohr argues, the mental image proposed by Heisenberg should be avoided. Later developments by Bell and Kochen-Specker shows that a model that contains the features used for the Heisenberg microscope is in principle possible but must necessarily be nonlocal and contextual. In this paper we will re-examine the measurement process within a restriction of QM known as Stabilizer QM (SQM), that still exhibits for example Greenberger-Horne-Zeilinger nonlocality and Peres-Mermin contextuality. The re-examination will use a recent extension of SQM, the Contextual Ontological Model (COM), where the system state gives a complete description of future measurement outcomes reproducing the quantum predictions, including the mentioned phenomena. We will see that the resulting contextual Heisenberg microscope back-action can be completely described within COM, and that the associated randomness originates in the initial state of the pointer system, exactly as in the original description of the Heisenberg microscope. The presence of contextuality, usually seen as prohibiting ontological models, suggests that the contextual Heisenberg microscope picture could perhaps be enabled in general QM.

Quantum reservoir computing offers a promising approach to the utilization of complex quantum dynamics in machine learning. Statistical noise inevitably arises in real settings of quantum reservoir computing (QRC) due to the practical necessity of taking a small to moderate number of measurements. We investigate the effect of statistical noise in spin-network QRC on the possible performance benefits conferred by quantumness. As our measures of quantumness, we employ both quantum entanglement, which we quantify by the partial transpose of the density matrix, and coherence, which we quantify as the sum of the absolute values of the off-diagonal elements of the density matrix. We find that reservoirs which enjoy a finite degree of quantum entanglement and coherence are more stable against the adverse effects of statistical noise on performance compared to their unentangled, incoherent counterparts. Our results thus indicate that the potential benefit reservoir computers may derive from quantumness depends on the number of measurements used for training and testing, and that statistical noise, albeit detrimental on the whole, may leave quantum reservoirs in a stronger position relative to less quantum ones. These findings not only emphasize the importance of incorporating realistic noise models, but also suggest that the search for computational regimes that benefit from quantumness may be aided rather than impeded by the practical constraints of implementation within existing machines.

This paper investigates the economic impact of vehicle-home-grid integration through an online optimization algorithm that manages energy flows between an electric vehicle, a household, and the electrical grid. The algorithm exploits vehicle-to-home (V2H) for self-consumption and vehicle-to-grid (V2G) for energy trading, adapting in real-time via a hybrid long short-term memory (LSTM) network for household load prediction and a nonlinear battery degradation model including cycle and calendar aging. Simulations show annual economic benefits up to EUR 3046.81 compared to smart unidirectional charging, despite a modest 1.96% increase in battery aging. Even under unfavorable market conditions, with no V2G revenue, V2H alone provides yearly savings of EUR 425.48. Sensitivity analyses on battery capacity, household load, and price ratios confirm the consistent benefits of bidirectional energy exchange, highlighting the role of EVs as active energy nodes for sustainable management.

We present a detailed study of the curvature and symplectic asphericity properties of symmetric products of surfaces. We show that these spaces can be used to answer nuanced questions arising in the study of closed Riemannian manifolds with positive scalar curvature. For example, we prove that symmetric products of surfaces sharply distinguish between two distinct notions of macroscopic dimension introduced by Gromov and the second-named author. As a natural generalization of this circle of ideas, we address the Gromov--Lawson and Gromov conjectures in the Kaehler projective setting and draw new connections between the theories of the minimal model, positivity in algebraic geometry, and macroscopic dimensions.

High-transition-temperature ($T_{C}$) superconductivity is recently discovered in Ruddlesden-Popper (RP) nickelate films with extraordinarily strong oxidation. While investigating phase diagrams is essential for uncovering the superconducting mechanism, the oxygen-tuned superconductor-insulator transition (SIT) in RP nickelates differs fundamentally from that in cuprates or iron-based systems. Here, we unveil the evolution of electronic structure in RP bilayer nickelate thin films across the SIT, combining angle-resolved photoemission spectroscopy (ARPES) and X-ray absorption spectroscopy (XAS) for both occupied and unoccupied states. In the superconducting state, a coherent quasiparticle band near Fermi level ($E_{F}$) coexists with an incoherent waterfall feature at high energy, paralleling that in cuprates. Approaching the insulating state with oxygen deficiency, the spectral weight of the occupied coherent quasiparticle band is gradually suppressed, accompanied by pronounced density of states redistribution and orbital reconfiguration in unoccupied states. These results reveal the electronic origin of the SIT in the phase diagram, which transcends carrier doping effects and oxygen vacancy states. Our findings point to a decisive role of oxygen in shaping the essential electronic landscape of RP bilayer nickelates, offering crucial insights into the superconducting mechanism.

A set of vertices $X\subseteq V$ in a simple graph $G(V,E)$ is irredundant if each vertex $x\in X$ is either isolated in the induced subgraph $G[X]$ or else has a private neighbor $y\in V\setminus X$ that is adjacent to $x$ and to no other vertex of $X$. The \emph{mixed Ramsey number} $t(m,n)$ is the smallest $N$ for which every red-blue coloring of the edges of $K_N$ has an $m$-element irredundant set in the blue subgraph or an $n$-element independent set in the red subgraph. The irredundant Ramsey number $s(m,n)$ is the smallest $N$ for which every red-blue coloring of the edges of $K_N$ has an $m$-element irredundant set in the blue subgraph or an $n$-element irredundant set in the blue subgraph. In this paper, we determine $t(3,n)$ and $s(3,n)$ up to a constant factor by showing that $t(3,n)=O\left(n^{5/4}/{\log{n}}\right)$, which improved the best upper bound due to Rousseau and Speed in [Comb. Probab. Comput. 12 (2003), 653-660]. As an application, we verify a conjecture for $m=4$ proposed by Chen, Hattingh, and Rousseau in [J. Graph Theory 17(2) (1993), 193-206].

In tomographic cosmic-shear observations, the BNT (Bernardeau, Nishimichi, Taruya) transform, Bernardeau et al. (2014), allows to build weak lensing transformed maps for which the contribution from low redshift lenses is nulled. As this transformation depends specifically on the expansion rate of the Universe but is independent of the matter distribution properties, it can be leveraged to extract information from large-scale structure probes at arbitrary non-linear scales, providing constraints on cosmological background evolution. We demonstrate this by proposing a specific null test for stage IV weak lensing projects. Using a Fisher matrix analysis and parameter sampling, we show that this approach can substantially enhance constraints on the dark energy equation of state. Notably, we find that shape noise currently limits this method's effectiveness making significant improvement possible in future designs. A detailed analysis of our null test in the context of the Euclid mission is presented in a companion paper Touzeau et al. (2025).

Direct data-driven control methods are known to be vulnerable to uncertainty in stochastic systems. In this paper, we propose a new robust data-driven predictive control (DDPC) framework. By analyzing non-unique solutions to behavioral representation, we gain insight into the inherent lack of robustness in subspace predictive control (SPC) and its projection-based regularized variant. This stimulates us to construct an uncertainty set that captures all admissible output trajectories deviating from nominal subspace predictions, which results in a min-max robust formulation of DDPC that endows control sequences with robustness against such unknown deviations. We establish theoretical performance guarantees under bounded additive noise and develop tractable convex reformulations. To mitigate the conservatism of robust design, a feedback robust DDPC scheme is further proposed by incorporating an affine feedback policy. Simulation studies show that the proposed methods effectively robustify SPC and outperform the projection-based regularization.

We present a polynomial-time classical algorithm for estimating expectation values of arbitrary observables on typical quantum circuits under any incoherent local noise, including non-unital or dephasing. Although previous research demonstrated that some carefully designed quantum circuits affected by non-unital noise cannot be efficiently simulated, we show that this does not apply to average-case circuits, as these can be efficiently simulated using Pauli-path methods. Specifically, we prove that, with high probability over the circuit gates choice, Pauli propagation algorithms with tailored truncation strategies achieve an inversely polynomially small simulation error. This result holds for arbitrary circuit topologies and for any local noise, under the assumption that the distribution of each circuit layer is invariant under single-qubit random gates. Under the same minimal assumptions, we also prove that most noisy circuits can be truncated to an effective logarithmic depth for the task of {estimating} expectation values of observables, thus generalizing prior results to a significantly broader class of circuit ensembles. We further numerically validate our algorithm with simulations on a $6\times6$ lattice of qubits under the effects of amplitude damping and dephasing noise, as well as real-time dynamics on an $11\times11$ lattice of qubits affected by amplitude damping.

We argue that rotation of a thin superconducting cylinder can increase the critical superconducting temperature substantially. A purely rotational effect originates from the tendency of a steadily rotating mechanical system to maximize its moment of inertia. A condensation of Cooper pairs in a rotating cylinder decouples a part of the normal electron fraction from rotation, thus producing a circulating electric current of an uncompensated electric charge of lattice ions. The current produces the magnetic field that stores energy of rotation, thus increasing the moment of inertia. In the presence of an external magnetic field, another enhancement effect originates from the interaction energy of the dipole magnetic moment of the normal component with the background magnetic field. In both cases, rotation of the cylindrical shell promotes the formation of condensate that decouples from mechanical rotation. We give quantitative estimates for a thin cylinder of aluminum.

In this work, we apply the DFT+U approach for a detailed ab initio study of the refined structure of the low-temperature phase of magnetite [M. S. Senn et al., Nature 481, 173 (2012)]. We compare the electronic properties of this structure and several alternatives with respect to the presence of trimeron ordering and the bandgap properties. The connection of the trimeron arrangement with site-selective doping of magnetite is discussed. Calculations of the polaron hopping energy allow us to make one step forward toward understanding the complex interplay of polaronic and bandgap contributions to electronic properties of the magnetite.

A point-like defect in a uniform current-carrying conductor induces a dipole in the electrochemical potential, which counteracts the original transport field. If the mean free path of the carriers is much smaller than the size of the defect, the dipole results from the purely diffusive motion of the carriers around the defect. In the opposite limit, ballistic carriers scatter from the defect$-$for this situation, Rolf Landauer postulated the emergence of residual resistivity dipoles that are independent of the defect size and thus impose a fundamental limit on the resistance of the parent conductor. Here, we study resistivity dipoles around holes of different sizes in two-dimensional Bi films on Si(111). Using scanning tunneling potentiometry to image the dipoles, we find a crossover from linear to constant scaling behavior of their amplitudes with defect size, manifesting the transition from diffusive to Landauer dipoles. The extracted parameters of the transition allow us to estimate the Fermi wave vector and the carrier mean free path in our Bi films.

Pre-smoothing is a technique aimed at increasing the signal-to-noise ratio in data to improve subsequent estimation and model selection in regression problems. However, pre-smoothing has thus far been limited to the univariate response regression setting. However, there are many scientific applications in which interest lies in multi-response regression problems, particularly when the number of responses is large. Motivated by this setting, this article proposes a technique for data pre-smoothing based on low-rank approximation. We establish theoretical results on the performance of the proposed methodology, which show that in this large-response setting, the proposed technique outperforms ordinary least squares estimation with the mean squared error criterion, whilst being computationally more efficient than alternative approaches such as reduced rank regression. We quantify our estimator's benefit empirically in a number of simulated experiments. We also demonstrate our proposed low-rank pre-smoothing technique on real data arising from the environmental and biological sciences.

We formulate and partially prove a general conjecture providing necessary and sufficient conditions for the reality of the asymptotic spectrum of an arbitrary real banded block Toeplitz matrix. Additionally we present numerical experiments supporting it. This conjecture is a direct generalization of the already existing one in the case of banded Toeplitz matrices.

We study frequently recurrent unilateral and bilateral backward shift operators on Fréchet sequence spaces. We prove that if a backward shift admits a non-zero frequently recurrent vector, then it supports a dense set of such vectors, so that the operator is frequently recurrent. As a consequence, we provide two different characterizations for frequently recurrent backward shift operators and we show dense lineability of the set of the set of frequently recurrent vectors.

This paper proposes hybrid high-order eigensolvers for the computation of guaranteed lower eigenvalue bounds. These bounds display higher order convergence rates and are accessible to adaptive mesh-refining algorithms. The involved constants arise from local embeddings and are available for all polynomial degrees. Applications include the linear elasticity and Steklov eigenvalue problem.

In this work we prove global well-posedness for the massive Maxwell-Dirac system in the Lorenz gauge in $\mathbb{R}^{1+3}$, for small, sufficiently smooth and decaying initial data, as well as modified scattering for the solutions. Heuristically we exploit the close connection between the massive Maxwell-Dirac and the wave-Klein-Gordon equations, while developing a novel approach which applies directly at the level of the Dirac equations. The modified scattering result follows from a precise description of the asymptotic behavior of the solutions inside the light cone, which we derive via the method of testing with wave packets of Ifrim-Tataru.

We demonstrate that every point where X - a closed subset of R^n - is not Lipschitz Normally Embedded is approached by the medial axis of X.

Fake path injection is an emerging paradigm for inducing privacy over wireless networks. In this paper, fake paths are injected by the transmitters into a single-input multiple-output (SIMO) communication channel to obscure their physical location from an eavesdropper. The case where the receiver (Bob) and the eavesdropper (Eve) use a linear uniform array to locate the transmitter's (Alice) position is considered. A novel statistical privacy metric is defined as the ratio between the smallest (resp. largest) eigenvalues of Eve's (resp. Bob's) Cramér-Rao lower bound (CRB) on the SIMO channel parameters to assess the privacy enhancements. Leveraging the spectral properties of generalized Vandermonde matrices, bounds on the privacy margin of the proposed scheme are derived. Specifically, it is shown that the privacy margin increases quadratically in the inverse of the angular separation between the true and the fake paths under Eve's perspective. Numerical simulations validate the theoretical findings on CRBs and showcase the approach's benefit in terms of bit error rates achievable by Bob and Eve.

We revisit our argument that shows that parton distribution Functions (PDFs) in the MSbar{ scheme are non-negative in the perturbative region, with the main goals of elucidating its domain of validity and clarifying its theoretical underpinnings. We specifically discuss recent results proving that PDFs can turn negative at sufficiently low scale, we clarify quantitatively various aspects of our derivation of positivity in the perturbative region, and we provide an estimate for the scale above which PDF positivity holds.

Let $R$ be a commutative ring with identity and a fixed invertible element $q^{\frac{1}{2}}$. Let $\mathcal{S}_n$ denote the Kauffman bracket skein algebra of the $n$-holed disk $Σ_{0,n+1}$ over $R$. When $q+q^{-1}$ is invertible, in 2000 Przytycki and Sikora found a set of $n+{n\choose 2}+{n\choose 3}$ generators for $\mathcal{S}_n$; we show that the ideal of defining relations among these generators is generated by relations of degree $\le6$ supported by certain subsurfaces diffeomorphic to $Σ_{0,k+1}$ with $k\le 6$. When $q+q^{-1}$ is not invertible, a set of $2^n-1$ generators for $\mathcal{S}_n$ was known to Bullock in 1999; we show that the ideal of defining relations is generated by relations of degree $\le 2k+2$ supported by certain subsurfaces diffeomorphic to $Σ_{0,k+1}$ with $k\le n$. These results are substantial progresses towards answering Problem 1.92 (J) in the Kirby's list.

We investigate deterministic and randomized streaming algorithms for word problems in finitely generated groups and semigroups. For this we introduce the notion of a distinguisher: a randomized streaming algorithm that processes two input words in parallel and, with high probability, reaches identical memory states if the words represent the same element, and distinct states otherwise. We construct such distinguishers with low error probability using logarithmic, and in some cases doubly logarithmic, space. For example, our results apply to linear semigroups and to semigroups obtained (under suitable restrictions) via standard constructions such as graph products, wreath products, and semilattice decompositions. In case of commutative semigroups and cancellative nilpotent semigroups, we achieve space complexity $\mathcal{O}(\log \log n)$. We complement these upper bounds with lower bounds demonstrating that certain well-known semigroups do not admit sublinear-space distinguishers. This includes, for example, free inverse monoids of rank at least two and Thompson's group $F$. Finally, we study randomized streaming algorithms for subgroup membership problems in free groups and their direct products.

A finite group $G$ is called $k$-factorizable if for every ordered factorization $|G|=a_1\cdots a_k$ into integers each greater than $1$ there exist subsets $A_1,\dots,A_k\subseteq G$ such that $|A_i|=a_i$ for each $i$ and $G=A_1\cdots A_k$. The main results are as follows. 1. For every integer $k\geq3$ there exists a finite group $G$ such that $G$ is not $k$-factorizable. 2. Let $G$ be a finite group of order $4m$. If a Sylow $2$-subgroup of $G$ is elementary abelian, all involutions of $G$ are conjugate, and the centralizer of every involution has a normal Sylow $2$-subgroup, then $G$ has no factorization of the form $G=ABC$ with $|A|=|C|=2$ and $|B|=m$. 3. Only $8$ groups of order at most $100$ fail to be $k$-factorizable for some $k$.

Addition chains are a classical construction for fast exponentiation and related computation problems. In this paper, we study a chain for a fixed integer $n$ by decomposing each generator into a \emph{determiner} and a \emph{regulator} (gap). This viewpoint leads to explicit identities for two aggregate statistics of the chain: the sum of the determiners and the sum of the chain elements. We then derive the corresponding lower bounds by using the positivity of the regulators. In parallel, we establish an identity for the reciprocal sum of the chain, showing how the harmonic profile of the chain can also be written in terms of the same gap sequence. These identities provide a unified way to compare addition chains of the same target and length. The paper concludes with a balancing problem that asks for the chain(s) that minimize the difference between the arithmetic sum and the harmonic sum, together with a structural decomposition of that optimization objective.

This paper aims to establish a relation between the tangent cone of the medial axis of X at a given point a of R^n$ and the medial axis of the set of points in X realising the distance d(a,X). As a consequence, a lower bound for the dimension of the medial axis of X in terms of the dimension of the medial axis of m(a) is obtained. This appears to be the missing link to the full description of the medial axis' dimension. Further study of potentially troublesome points on the frontier of the medial axis is also provided, resulting in their characterisation in terms of the reaching radius.

This paper develops the notion of superquadracity defined by L.Birbrair and M.Denkowski for subsets of R^n. In this regard, the main theorem of the paper establishes the relation between the superquadracity and non-empty intersection of the set and the closure of its medial axis. The further investigation concerns non C1 smooth points of the set.

We prove that the contact graph of a 2-dimensional CAT(0) cube complex ${\bf X}$ of maximum degree $Δ$ can be coloured with at most $ε(Δ)=MΔ^{26}$ colours, for a fixed constant $M$. This implies that ${\bf X}$ (and the associated median graph) isometrically embeds in the Cartesian product of at most $ε(Δ)$ trees, and that the event structure whose domain is ${\bf X}$ admits a nice labeling with $ε(Δ)$ labels. On the other hand, we present an example of a 5-dimensional CAT(0) cube complex with uniformly bounded degrees of 0-cubes which cannot be embedded into a Cartesian product of a finite number of trees. This answers in the negative a question raised independently by F. Haglund, G. Niblo, M. Sageev, and the first author of this paper.

Accurate identification of Hamiltonian parameters is essential for modeling and controlling open quantum systems. In this work, we demonstrate that the multichannel Hankel alternative view of Koopman (mHAVOK) algorithm is a robust and reliable spectral data-driven method for retrieving Hamiltonian parameters from the evolution of first-moment observables in open quantum systems. The method relies on the discrete spectrum of the Koopman operator to obtain these parameters, which are computed using the mHAVOK algorithm; a theoretical connection to this affirmation is presented. The method is tested on noiseless quadratures of an open two-dimensional quantum harmonic oscillator and shown to retrieve oscillation frequencies, damping rates, nonlinear Kerr shifts, the qubit-photon coupling strength of a Jaynes-Cummings interaction, and the modulated frequency of a time-dependent Hamiltonian. The majority of the recovered parameters remained within 5\% of their actual values. Compared with Fourier and matrix-pencil estimators, our approach yields lower errors for dynamics with strong dissipation. Overall, these findings suggest that Koopman operator theory provides a practical framework for studying quantum dynamical systems.