Papers

We present an efficient algorithm for the construction of a holographic simple tree graph model that realizes a given entropy vector, subject to a specific “chordality” condition first introduced in arXiv:2412.18018. We further develop the toolkit of the correlation hypergraph, particularly in relation to coarse-graining and fine-graining of subsystems. We then use these techniques to take the first steps towards the generalization of this new algorithm to arbitrary (not necessarily simple) holographic tree graph models, and the “detection” of unrealizability of an entropy vector independently from the knowledge of holographic entropy inequalities.

Open-shell nanographenes offer a controlled setting to study correlated magnetism emerging from $\pi$-electron systems. Here, we study non-bipartite Fermi-Hubbard ladders describing oligo(indenoindene) molecules. These feature a gapped, weakly dispersing manifold of quasizero modes in their single-particle spectra, and we show that their low-energy properties can be effectively mapped onto an interacting set of spin-1/2 degrees of freedom. Using density matrix renormalization group simulations of the full Fermi-Hubbard model, we obtain their excitation spectra, entanglement profiles, and spin-spin correlations. We then construct optimized delocalized fermionic modes that act as emergent spins and demonstrate that their interactions are well described by a frustrated $J_1$-$J_2$ Heisenberg chain. This effective description clarifies how spin degrees of freedom arise and interact in non-bipartite nanographene ladders, providing a compact and accurate representation of their correlated behavior.

We investigate the quantum sensing performance of a dephasing qubit as a probe in Ohmic environments, characterized by the coupling strength $\eta$, the Ohmicity parameter $s$, and the cutoff frequency $\omega_c$ to be estimated. The performance is quantified by the dimensionless quantum signal-to-noise ratio $\mathcal{Q}$. We show that the evolution of $\mathcal{Q}$ with the scaled time $\omega_c t$ is independent of $\omega_c$, and peaks at an optimal time $t_{\text{opt}}$, yielding optimal sensitivity $\mathcal{Q}_{\text{opt}}$. We analyze how $\mathcal{Q}_{\text{opt}}$ depends on $\eta$, $s$ and the temperature $T$. Our results demonstrate that, for any Ohmic environment, provided that $\omega_c t_{\text{opt}} \ll 1$, $\mathcal{Q}_{\text{opt}}$ always reaches the upper bound: $\mathcal{Q}_{\text{max}} = 0.648$ at zero temperature, and consistently attains $\mathcal{Q}_{\text{max}}/4$ at high temperatures. Remarkably, we find that increasing the scaled temperature $T/\omega_c$ can enhance $\mathcal{Q}_{\text{opt}}$ by nearly two orders of magnitude compared to its zero-temperature counterpart for certain Ohmic environments. Our work reveals that temperature can serve as a resource to enhance sensing precision, as it accelerates the encoding of the cutoff frequency information into the probe state, thereby enabling optimal measurement within a short time window.

Contemporary quantum computers are inherently noisy, posing significant challenges for the development and testing of quantum software. Simplified or outdated noise assumptions can lead to incorrect assessments of program correctness, obscure debugging, and hinder cross-platform portability, creating a critical quantum software development gap. Providing accurate, practical noise characterisation is challenging as traditional reconstruction methods scale exponentially and rapidly become outdated. In this vision paper, we address this gap via a novel classical shadow tomography-based pipeline, SIMSHADOW, enabling efficient, continuously updatable noise fingerprinting from empirical observations, suitable for integration into quantum software development workflows, including testing and validation. We prototyped the pipeline to investigate fingerprints' ability to capture structured, interpretable noise and cross-platform discrepancies affecting quantum programs' behaviour to support realistic testing and debugging in future tools. Our evaluation with Qiskit and Cirq under widely used hardware-informed profiles, IBM Boston and Quantinuum H2, shows fingerprints exhibit channel-specific structure and yield interpretable heatmaps. We observed systematic cross-platform discrepancies under matched noise configurations, quantified by large Frobenius distances at a fraction of full tomography cost. On 69 MQTBENCH programs, larger fingerprint differences correlate with output distributions divergences, highlighting threats for testing and cross-platform debugging tasks.

The quantum dissipative time evolution of a fluxonium under a pulsed field (kicks) is studied numerically and analytically. In the classical limit the system dynamics is converged to a strange chaotic attractor. The quantum properties of this system are studied for the density matrix in the frame of Lindblad equation. In the case of dissipative quantum evolution the steady-state density matrix is converged to a quantum strange attractor being similar to the classical one. It is shown that depending on the dissipation strength there is a regime when the eigenstates of density matrix are localized at a strong or moderate dissipation. At a weak dissipation the eigenstates are argued to be delocalized being linked to the Ehrenfest explosion of quantum wave packet. This phenomenon is related with the Lyapunov exponent and Ehrenfest time for the quantum strange attractor. Possible experimental realisations of this quantum strange attractor with fluxonium are discussed.

This paper introduces a hidden quantum Markov models (HQMMs) framework to the Affleck-Kennedy-Lieb-Tasaki (AKLT) state-a cornerstone example of a symmetry-protected topological (SPT) phase. The model's observation system is the physical spin-1 chain, which emerges from a hidden spin-1/2 layer through well-defined quantum emission operation. We show that the underlying Markov dynamics caputure maximal entanglement through the use of significant channels relevant to the AKLT state. We also show that SPT order induces a covariance on the observation decoding channels. This establishes an additional bridge between the quantum Machine learning and many-body physics, with promising implication in topological order and quantum information.

Semiclassical gravity, in which a classical spacetime is sourced by the quantum expectation value of the stress-energy tensor, is a standard framework for describing the gravitational interaction of quantum matter. In the nonrelativistic limit this approach leads to the Schrödinger-Newton equation, which is often assumed to be consistent at least in the weak-field regime. In this work, we reexamine this assumption for spatial quantum superpositions of massive particles. We show that, when the quantum state is properly normalized, no modification of the Newtonian gravitational potential arises at leading order. However, at first post-Newtonian order the semiclassical coupling generically produces state-dependent contributions involving the mass density and the mass current of the superposition. These terms have a parametric scaling which is different from that of the corresponding relativistic corrections and which does not have Planck mass suppression. Our results therefore impose a strong post-Newtonian consistency constraint on deterministic semiclassical gravity, indicating that sourcing the metric solely by expectation values is insufficient to recover a consistent relativistic weak-field expansion.

Quantum Reservoir Computing (QRC) leverages the natural dynamics of quantum systems for information processing, without requiring a fault-tolerant quantum computer. In this work, we apply QRC within a hybrid quantum classical framework for image denoising. The quantum reservoir is implemented using a Rydberg atom array, while a classical neural network serves as the readout layer. To prepare the input, images are first compressed using Principal Component Analysis (PCA), reducing their dimensionality to match the size of the atom array. Each feature vector is encoded into local detuning parameters of a time-dependent Hamiltonian governing the Rydberg system. As the system evolves, it generates nonlinear embeddings through the measurement of observables across multiple time steps. These temporal embeddings capture complex correlations, which are fed into a classical neural network to reconstruct the denoised images. To evaluate performance, we compare this QRC-assisted model against a baseline architecture consisting of PCA followed by a dense neural network, trained under identical conditions. Our results show that the QRC-based approach achieves improved image sharpness and similar structural recovery compared to the PCA-based model. We demonstrate the practical viability of this framework through experiments on QuEra's Aquila neutral-atom processor, leveraging its programmable atom arrays to physically realize the reservoir dynamics.

Locally covariant algebraic quantum field theory (LCQFT) satisfies Einstein causality through microcausality and operational no-signalling, yet Bell-type correlations persist in entangled field states across spacelike regions. We demonstrate that this apparent tension reflects a fundamental covariance obstruction: no assignment of classical past variables can simultaneously be covariant under spacetime embeddings, screen off quantum correlations, and reproduce AQFT statistics. This obstruction is distinct from dynamical nonlocality or signalling violations. We formalize this as a no-go theorem in the category-theoretic framework of LCQFT, showing that Bell's notion of local causality – requiring factorization conditioned on a common past – is structurally incompatible with diffeomorphism covariance. The failure of Bell locality thus reflects not a breakdown of relativistic causality but the impossibility of embedding quantum correlations into a classical causal framework without introducing preferred foliations or non-covariant beables. This clarifies the conceptual status of nonlocality in relativistic quantum theory.

We develop a variational regularisation framework that enables analytical solutions of the stationary de~Broglie–Bohm wave equation. The formulation begins with a Fisher-information-augmented action functional for the probability density and phase fields, yielding the Madelung (Hamilton–Jacobi and continuity) equations and, upon complex recombination, a Schrödinger-type equation with a parametric information coupling $\mu$. Beyond this density-based formulation, we introduce a variational regularisation scheme for the de~Broglie–Bohm equations that combines a global Fisher-information regularisation at the level of the action functional with a shell-level regularisation arising from stationary flux closure. This reduction isolates the regularisation mechanism in the spatial momentum flow and yields constrained Euler–Lagrange equations governing admissible amplitude configurations. The resulting first integral possesses an elliptic structure whose admissible asymptotic branch enforces a universal canonical relation $p(x)x \to \mu/2$ near amplitude zeros. The framework yields closed-form analytical solutions for standard potentials and reveals a systematic inverse-square regularising term in the effective potential. The associated elliptic discriminant defines a geometric length scale that, for $\mu=\hbar$, naturally reduces to the reduced Compton wavelength. Canonical Bohmian regularisation therefore appears as a variational admissibility condition on density dynamics, producing structurally stable analytical branches and modified yet consistent energy spectra within stationary dBB mechanics.

Some of the problems connected with the interpretation of quantum mechanics are enumerated, in particular those related to some well known paradoxes and, above all, to the measurement process. We then show how the so called "Physics Laboratory Assumption" introduced in [1], which considers as "observables” only the self-adjoint operators corresponding to existing measuring instruments, can propose a new perspective on the aforementioned problems and can replace the wavefunction collapse postulate. [1] Luigi E. Picasso, "On the Concept of State in Quantum Mechanics: Another Way to Decoherence?” Int. J. Theor. Phys. 62 (2), (2023)

We introduce a method for constructing global approximations to correlation functions of strongly interacting quantum field theories, starting from perturbative results. The key idea is to employ interpolation method, such as the two-point Padé expansion, to interpolate the weak and strong coupling expansions of correlation function. We benchmark this many-body interpolation approach on two prototypical models: the lattice $\phi^4$ field theory and the 2D Hubbard model. For the $\phi^4$ theory, the resulting two point Padé approximants exhibit uniform and global convergence to the exact correlation function. For the Hubbard model, we show that even at second order, the Padé appproximant already provides reasonable characterization of the Matsubara Green's function for a wide range of parameters. Finally, we offer a heuristic explanation for these convergence properties based on analytic function theory.

Universal QRAM (U-QRAM) is a fixed, data-independent unitary interface that implements coherent random-access reads relative to a designated computational "truth-table" basis on the memory register. This work studies restricted-access inference: the memory register is persistent but inaccessible, while an experimenter may prepare and measure only accessible registers and may invoke the fixed read interaction. Allowing the memory to be in an arbitrary quantum state (pure or mixed, possibly entangled with an inaccessible reference system, or a coherent superposition of truth tables), we establish a sharp, protocol-independent limitation of read-only access. For any finite-query protocol – including arbitrary accessible ancillas, intermediate measurements, adaptivity, and general CPTP processing between queries – the induced output state on the accessible registers depends on the memory state only through its diagonal in the truth-table basis. Equivalently, read-only access factors through dephasing (pinching) in that basis; coherences between distinct truth tables are operationally invisible. Consequently, every memory-hypothesis testing task reduces to a standard state-discrimination problem on the accessible registers, and the minimum-error optimal measurement is characterized by Helstrom theory. We illustrate the framework with three explicit examples: (i) the phase-kickback reduction recovering the one-query Bernstein-Vazirani/Deutsch-Jozsa geometry, (ii) a minimal Helstrom instance with optimal success probability 3/4, and (iii) perfect indistinguishability of relative phases in entangled truth-table superpositions.

Photonic multidimensional quantum networks (MDQN), where individual subsystems are encoded using multiple degrees of freedom and photons, are an emerging platform for quantum algorithms because they offer high scalability. The distribution of non-classical and non-local correlations between the individual subsystems in an MDQN is of fundamental interest for many quantum protocols. Interestingly in an MDQN, the inseparability of two subsystems underlying entanglement can occur both between multiple distinct photons as well as between individual degrees of freedom associated with a single photon. In this work, we investigate the entanglement transfer enabled by the interplay of both entanglement between two distinct photons as well as inseparability between multiple degrees of freedom. For this purpose, we subject one photon of a polarization entangled two-photon pair to a discrete-time quantum walk introducing the position subsystem of the quantum walk as a third subsystem with qudit encoding. Here we study the resulting transfer of entanglement from the polarization degree of freedom, representing qubit encoding, towards the position degree of freedom, representing quidt encoding, via partial state tomography and correlation measurements.

The question of certifying quantum nonlocality under a relaxation of the assumptions in the Bell theorem has gained traction, with potential for device-independent applications under weak seeds and cross-talk. Recently, it was shown that quantum nonlocality can be certified even under a simultaneous arbitrary (but not full) relaxation of the assumptions of Measurement Independence (MI) and Parameter Independence (PI), using states of local dimension $d = poly((1-\epsilon)^{-1})$ for an $\epsilon \in [0,1)$-relaxation. Here, we derive three results strengthening the state-of-art. Firstly, we show that states of constant local dimension $d$ are already sufficient to certify quantum nonlocality under arbitrary MI and PI relaxation, albeit in a non-robust manner. Secondly, and as a theoretical paradigm to derive the above, we introduce the notion of measurement-dependent parameter-dependent locality as the set of input-output behaviors under simultaneous relaxations of measurement and parameter independence. We provide a rigorous characterisation of the vertices of the polytope of joint input-output behaviors that obey a $\mu$-relaxation of MI and $\epsilon$-relaxation of PI. We highlight a relation between nonlocality certification under PI relaxation and that under detection inefficiencies by pointing out alternative extremal correlations to the Eberhard correlations that also allow to achieve detection efficiency of $\eta = 2/3$ in the two-input scenario. Finally, we study the implication of the relaxed assumptions for device-independent randomness certification. We analytically derive the quantum guessing probability for one player's outcomes in the CHSH Bell test, as a function of the noise in the test as well as of a leakage of an average amount of $I(X:B) < 1$ bits of input information per measurement round.

Threat detection models in cybersecurity must keep up with shifting traffic, strict feature budgets, and noisy hardware, yet even strong classical systems still miss rare or borderline attacks when the data distribution drifts. Small, near-term quantum processors are now available, but existing work rarely shows whether quantum components can improve end-to-end detection under these unstable, resource constrained conditions rather than just adding complexity. We address this gap with a hybrid architecture that uses a compact multilayer perceptron to compress security data and then routes a few features to 2-4 qubit quantum heads implemented as quantum support vector machines and variational circuits. Under matched preprocessing and training budgets, we benchmark these hybrids against tuned classical baselines on two security tasks, network intrusion detection on NSL-KDD and spam filtering on Ling-Spam datasets, and then deploy the best 4-qubit quantum SVM to an IBM Quantum device with noise-aware execution (readout mitigation and dynamical decoupling). Across both datasets, shallow quantum heads consistently match, and on difficult near-boundary cases modestly reduce, missed attacks and false alarms relative to classical models using the same features. Hardware results track simulator behavior closely enough that the remaining gap is dominated by device noise rather than model design. Taken together, the study shows that even on small, noisy chips, carefully engineered quantum components can already function as competitive, budget-aware elements in practical threat detection pipelines.

We present a multifractal analysis of time series data obtained by repeatedly running a single-qubit quantum circuit on IBM superconducting quantum computers, in which the measurement outcomes are recorded as the number of zeros. By applying advanced signal processing techniques, including the wavelet leader method and multifractal detrended fluctuation analysis, we uncover strong multifractal behavior in the output data. This finding indicates that the temporal fluctuations inherent to quantum circuit outputs are not purely random but exhibit complex scaling properties across multiple time scales. The multifractal nature of the signal suggests the possibility of tailoring filtering strategies that specifically target these scaling features to effectively mitigate noise in quantum computations. Our results not only contribute to a deeper understanding of the dynamical properties of quantum systems under repeated measurement but also provide a promising avenue for improving noise reduction techniques in near-term quantum devices.

We investigate the dynamics of two trapped ions interacting with a common thermal reservoir, focusing on how cross-correlated dissipation influences heating, steady-state behavior, and parameter sensitivity. Starting from a microscopic system–reservoir model, we derive the corresponding Heisenberg–Langevin equations and show that reservoir-induced correlations generate collective decay channels and, when the cross-damping rate matches the local damping, a decoherence-free normal mode that preserves memory of the initial excitations. Using the Fisher information associated with motional population measurements, we identify the parameter regimes in which cross-damping enhances the estimability of both system and reservoir properties. For nonclassical initial states, we also show that reservoir-mediated correlations can generate or maintain entanglement, with the strongest effects occurring near the decoherence-free condition.

Modern experiments in resonators are moving to ever more extreme quantum regimes, posing major challenges to established theoretical approaches, such as so-called few-mode models. While these models have driven major insights for traditional regimes, they are now hitting their limitations for highly open cavities and extended systems, as encountered in cavity experiments with molecules and solid-state systems. Here, we present a novel method that significantly extends the conceptual underpinning of these discrete-mode models, promoting them to a systematic treatment. We develop an ansatz which allows to quantize the resonator's resonances with position-resolved discrete modes, thus naturally incorporating losses in the formalism. Such a construction effectively unifies key ideas from pseudomodes and quantized quasi-normal modes theory. We further present a criterion for construction of the ansatz parameters at every point in space, and semi-analytically benchmark the resulting solution for a paradigmatic one-dimensional example resonator.

Combinatorial optimization is considered a promising class of problems in which quantum computers can show significant advantages. However, problems of practical relevance typically have more variables than current or foreseeable quantum computers have qubits. Here we introduce a divide and conquer approach that partitions the optimization problem into subgraphs that can be represented on smaller quantum processors. We then find all states of the subgraphs that can possibly be part of the solution to the entire problem by determining the cost or energy ranges in which the local subgraph energies of these states must be contained. This allows us to reduce the problem by only considering the subspace spanned by these states. We then recombine the system using a binary encoding for each subgraph with a local energy ordering. This process can be iterated until no further reduction is possible. We also find that the number of necessary qubits can be reduced further when only retaining states in a fraction of the relevant energy range at very little expense in terms of approximation ratio to the global ground state. In numerical simulations, we find that our approach allows us to solve combinatorial optimization problems on weighted random 3-regular graphs with $|\mathcal{V}|=40$ discrete variables on $\sim |\mathcal{V}| / 4$ qubits while retaining a possible approximation ratio of $\sim99.9\%$. We also observe an increasing reduction with larger system sizes.

Gate-based quantum image processing is constrained by qubit scarcity and the high overhead of quantum state preparation, limiting its applicability to realistic geometric data. We introduce a quantum-native framework for image matching on neutral-atom analog quantum computers that advances our earlier Sparse-Dots Representation (SDR) approach. A classical pre-processing pipeline – Sobel edge extraction followed by the Ramer–Douglas–Peucker (RDP) algorithm – converts an input image into a geometrically faithful Sparse-Dots point cloud of substantially fewer atoms. This atom layout is virtually embedded into the programmable tweezer array of QuEra's Aquila device via its Bloqade SDK, where the image geometry is encoded physically in the distance-dependent van der Waals interaction term of the Rydberg Hamiltonian. After time-evolution, we extract the many-body fingerprint of each image using two observables – the Pearson-normalized two-site correlation matrix which encodes the blockade-induced correlation structure of the quantum state, and the two-dimensional static structure factor evaluated on a fixed wavevector grid, yielding a fingerprint vector of constant length regardless of atom count. In Stage~1, image matching is performed by cosine similarity on the fingerprint vectors, a scale-invariant metric appropriate for Fourier-domain descriptors. In Stage~2, this approach is extended to quantum reservoir computing~(QRC) to enable machine learning via dramatically reduced training data and training cycles, as a preliminary proof-of-concept. Simulations using the Bloqade software stack confirm successful matching of industrial objects, often with fewer than 24 atoms. To our knowledge, this constitutes the first application of the static structure factor – a condensed-matter quantum observable – as an image retrieval descriptor in an analog quantum computing context.

We develop a symmetry-adapted multipolar $\mathbf{k}\cdot\mathbf{p}$ theory close to the bulk $\Gamma$ point for time-reversal-symmetric, noncentrosymmetric $C_{3v}$ crystals in the strong atomic spin-orbit-coupling ($jj$-coupling) limit. Using a $j\in\{1/2,3/2,5/2\}$ multiplet basis appropriate for heavy-element p- and d-bands, we systematically construct all symmetry-allowed spin-orbit coupling terms up to fifth order in momentum and generalize the usual spin texture to a total-angular-momentum texture. For $j>1/2$, multipolar spin-orbit coupling qualitatively reshapes Fermi surfaces and makes the topology of Bloch states band dependent. This leads to anisotropic high-$j$ textures that go beyond a single Rashba helix. We classify these textures by their total-angular-momentum vorticity $W_{n}$ for every energy band and identify distinct $|W_{n}|=1,2,5$ phases. We show that their crossovers generate enhanced and nonmonotonic current-induced spin-polarization responses, namely the Edelstein effect, upon tuning the chemical potential. Our results provide a symmetry-based framework for analyzing and predicting multipolar spin-orbit coupling, total-angular-momentum textures, and spintronic responses in heavy-element materials without an inversion center.

The symplectic group Sp(n) acts on phase space while the unitary representation of its double cover, Mp(n), the metaplectic group, acts on functions defined on configuration space. We will construct an extension Mp(n) of Mp(n) acting on square integrable functions on phase space. This is performed using previous results of ours involving explicit expressions of the twisted Weyl symbols of metaplectic operators and Bopp pseudodifferential operators, which are phase space extensions of the usual Weyl operators.

We introduce a locally symplectic-invariant quantifier of correlations between arbitrary bosonic Gaussian modes, with particular emphasis on quantum field theory. The quantity, denoted by~$\mathcal{D}^{\mathrm{sym}}$, admits a simple geometric interpretation as the symmetric overlap between each mode and the purification partner of the other, providing a direct geometric characterization of how correlations are distributed between modes. We derive a necessary and sufficient criterion for two-mode Gaussian entanglement in terms of $\mathcal{D}^{\mathrm{sym}}$, placing on firm quantitative footing the intuition that the entanglement of a localized mode is encoded in the spatial support of its purification partner. We demonstrate the framework for wavepacket modes of a scalar quantum field in Minkowski spacetime (illustrating how the geometry of partner modes reveals the spatial structure of quantum correlations) and discuss extensions to multimode systems and mixed Gaussian states.

I outline a neo-Bohrian interpretation of quantum mechanics – a view of quantum mechanics that accords with the core insights in Bohr's thinking, with a twist that justifies the prefix `neo.' In a second part of the paper, I show how von Neumann's work on infinite direct products provides a theoretical framework that deflates the measurement problem and justifies Bohr's insistence on the primacy of classical concepts.

Computing spectral functions in large, non-periodic super-moiré systems remains an open problem due to the exceptionally large system size that must be considered. Here, we establish a tensor network methodology that allows computing momentum-resolved spectral functions of non-interacting and interacting super-moiré systems at an atomistic level. Our methodology relies on encoding an exponentially large tight-binding problem as an auxiliary quantum many-body problem, solved with a many-body kernel polynomial tensor network algorithm combined with a quantum Fourier transform tensor network. We demonstrate the method for one and two-dimensional super-moiré systems, including super-moiré with non-uniform strain, interactions treated at the mean-field level, and quasicrystalline super-moiré patterns. Furthermore, we demonstrate that our methodology allows us to compute momentum-resolved spectral functions restricted to selected regions of a super-moiré, enabling direct imaging of position-dependent electronic structure and minigaps in super-moiré systems with non-uniform strain. Our results establish a powerful methodology to compute momentum-resolved spectral functions in exceptionally large super-moiré systems, providing a tool to directly model quantum twisting microscope experiments in twisted van der Waals heterostructures.

Hybrid quantum-classical algorithms have begun to leverage quantum devices to efficiently represent many-electron wavefunctions, enabling early demonstrations of molecular simulations on real hardware. A key prerequisite for scalable quantum chemistry, however, is size consistency: the energy of non-interacting subsystems must scale linearly with system size. While many algorithms are theoretically size-consistent, noise on quantum devices may couple nominally independent subsystems and degrade this fundamental property. Here, we systematically evaluate size consistency on quantum hardware by simulating systems composed of increasing numbers of non-interacting H$_{2}$ molecules using optimally shallow unitary circuits. We find that molecular energies remain size-consistent within chemical accuracy for an estimated 118 and 71 H$_{2}$ subsystems for one- and two-qubit unitary designs, respectively, demonstrating that current quantum devices preserve size consistency over chemically relevant system sizes and supporting the feasibility of scalable, noise-resilient simulation of strongly correlated molecules and materials.

Uncertainty and entanglement are both profound and key concepts in quantum theory. For three observables, the tightest uncertainty constants for both product and summation forms are revealed. In this work, we give an alternative proof for three observables, also with a physical interpretation of the uncertainty constants. Our results show that such constants are intimately connected with the distinguishment between separable and entangled states.

The nonequilibrium thermodynamics of interacting quantum many-body systems is investigated within the framework of thermal time-dependent density functional theory using a generalized linear-response formulation for the full quantum work statistics. A first-principles route is established to reconstruct the relaxation function that underlies linear-response theory, thereby moving beyond phenomenological descriptions and enabling a consistent evaluation of all moments of the dissipated-work distribution in interacting systems. The predictive power of the approach is demonstrated for the Hubbard model subject to a staggered external potential, where the evolution of the relaxation dynamics during the Mott-to-band-insulator crossover reveals how distinct many-body phases shape the out-of-equilibrium thermodynamic response. These results provide a microscopic and transferable framework for quantum thermodynamics in correlated systems, bridging thermal density functional theory and nonequilibrium work statistics.

Source-independent quantum secret sharing (SI QSS), while essential for secure multiuser cryptographic operations in quantum networks, faces significant implementation challenges stemming from the inherent complexity of generating and distributing multipartite entangled states. Recently, a resource-efficient SI QSS protocol utilizing entangled photon pairs combined with a postmatching method has been proposed to address this limitation. In this Letter, we report an experimental demonstration of this protocol using high-fidelity polarization-entangled photon pairs in a star topology. For a three-user network, we obtain secure key rates of 21.18, 4.69, and 1.71 kbps under single-user channel losses of 7.6, 10.9, and 12.9 dB respectively. Furthermore, under conditions of equal channel loss per user, we achieve secure key rates of 6.97, 6.46, and 5.88 kbps for three-, four-, and five-user scenarios respectively. These results demonstrate the advantageous independence of the key rate from the number of users. Our work paves the way for large-scale deployment of SI QSS in multiuser quantum networks.