Papers

The quest for superconductivity created by light extends for more than half a century, yet direct evidence of a true zero-resistance state - whose macroscopic quantum phase coherence is both created and controlled by light - has remained elusive. Here we report for the first time on a complex but robust light-programmable superconducting (LiPS) state at an aluminium-silicon heterojunction that is created and fully controlled with femtosecond laser pulses. The superconducting critical temperatures - ranging from 1.8 to 8.5 K, can be increased or erased at will by the application of tailored pulse sequences. At low temperatures the LiPS state shows features characteristic of a Berezinski-Kosterlitz-Thouless topological transition, but another distinct state appears at temperatures above 2 K, which shows clear signatures of quantum phase disorder. In the presence of a magnetic field we observe behaviour characteristic of vortex pinning and creep consistent with the 2-dimensional (2D) nature of the phase coherent system. The origin of the LiPS effect is attributed to light pulse control of the Moire-like superlattice of misfit dislocations (MDs) arising from discommensurations between the Al and Si lattices which is visible by high-resolution electron microscopy. We show how light pulses can be used to control the superlattice periodicity and highlight the appearance of topologically protected soliton-like kinks along the dislocation lines, important for imparting controllable metastability to the system. The demonstration of LiPS paves the way for designing metastable superconducting devices with controllable phase-coherence, enabling applications such as light-engineered quantum circuits, local gap tuning in quantum processors, and optically switchable superconducting devices.

Heterogeneous integration provides a promising route to combine semiconductor quantum dot devices and superconducting microwave circuits, while allowing each component to be fabricated using an optimized process flow. Here, we demonstrate a flip-chip integrated platform for dispersive readout of silicon metal-oxide semiconductor (SiMOS) quantum dot devices. A SiMOS double quantum dot chip is bonded to a superconducting aluminum resonator chip using indium bump interconnects to enable microwave coupling to the quantum dot gate. We show that the developed flip-chip process is compatible with cryogenic operation of both the SiMOS device and the superconducting resonator, and demonstrate resonator-based detection of charge transitions in the quantum dot system. The readout signal-to-noise ratio follows a dependence of $\sqrt{t}$ with the integration time, reaching SNR = 1 at an integration time of approximately 0.3 ms. These results establish flip-chip bonding as a viable integration approach for SiMOS quantum dot devices operating at both dc and microwave frequencies, with potential applications for resonator-based techniques such as spin-photon coupling.

We study the Lyapunov spectrum scaling of thermal weakly-nonlinear unitary maps in the presence of quasiperiodic potentials. We search for the crossover from long-range to short-range scaling as the localization length {\xi} decreases and compare the details to the case of uncorrelated Anderson disorder [Phys. Rev. Res. 6 L012064 (2024)]. A comparative statistical analysis of the eigenstates for the linear case shows that quasiperiodicity has a stronger localization impact at the same value of {\xi}. Therefore we expect that the scaling crossover should be enhanced as well. However, the numerical analysis shows that it is strongly delayed as compared to Anderson disorder, and is observed at anomalously small values of {\xi}. These findings hint at the potential impact of long range correlations of quasiperiodic localized eigenstates, which persist in the presence of interactions even in the case of integrability breaking and thermalization.

Community structures are common in real networks, and extracting them provides valuable insight in applications ranging from drug discovery to market segmentation. Overlapping community detection (OCD) is the task of clustering networked data in which nodes may belong to multiple clusters. Existing OCD algorithms often struggle to achieve a suitable balance between detection quality and scalability. We, therefore, propose Highway, a scalable OCD algorithm that exploits the sparse backbone of the input network to perform efficient community inference. We used 728 Lancichinetti-Fortunato-Radicchi benchmark networks to compare Highway and its ablated version against 10 existing OCD algorithms. Our results, based on five performance measures, demonstrate a competitive performance for Highway. It ranks first in overlapping normalized mutual information with a 6.9% improvement over the strongest baseline. It also ranks second in all the other four performance measures. These comparative results suggest that Highway coupled with its backbone procedure offers a suitable accuracy-efficiency trade-off. The Highway algorithm is open-source and available as part of the CDlib library.

Nonlinear thermodynamic computers based on Langevin dynamics exploit thermal fluctuations as a physical substrate for computation. Recent work has shown that quartic-confined fluctuating degrees of freedom can act as thermodynamic neurons capable of nonlinear function approximation at finite observation times. Here we extend this paradigm from mean-only readout to moment-resolved readout. Instead of representing each driven reservoir solely by its first moment, we construct a response vector from the elementwise raw polynomial moments \(\mathbb{E}[\bm{x}]\), \(\mathbb{E}[\bm{x}^{\odot 2}]\), and \(\mathbb{E}[\bm{x}^{\odot 4}]\). These observables combine displacement and central-shape contributions and are naturally aligned with the linear, quadratic, and quartic terms of the local driven dynamics. We further introduce a heterogeneous multi-reservoir architecture in which three reservoirs with distinct initialization and training histories form a joint \(2304\)-dimensional response representation. Under the fixed MNIST \(60000/10000\) reproduction protocol, feature-level fusion achieves the best observed accuracy of \(9695/10000=96.95\%\), compared with \(9682/10000=96.82\%\) for the strongest single-reservoir model and \(9684/10000=96.84\%\) for equal-weight logit averaging. An exact paired McNemar test does not establish a statistically significant improvement over the strongest single reservoir, but the ablation and wrong-set overlap results provide suggestive evidence of complementary classification errors. These results motivate higher-order polynomial-moment readout and reservoir heterogeneity as candidate design principles for finite-time Langevin computing.

Machine-learning force fields (MLFFs) are reliable only near their training distribution, making efficient construction of diverse training sets a major bottleneck for both train-from-scratch and foundation fine-tuning workflows. Active learning can reduce this cost, but standard model-committee uncertainty is impractical for foundation MLFFs because each committee member requires a separate fine-tuning run. We present an active-learning workflow based on last-layer-projection regression (LLPR), a forward-pass-cheap per-configuration uncertainty estimator. Across molecular, condensed-phase, and electrolyte systems, LLPR identifies compact, high-value training sets that recover full-data accuracy using only a small fraction of electronic-structure labels. In foundation-model fine-tuning, LLPR-selected configurations reach the full-pool fine-tuning ceiling with substantially fewer labels than random selection. In iterative electrolyte fine-tuning, LLPR detects unphysical local coordination before DFT labelling, provides an absolute force-error threshold, and enables automatic termination of the learning loop. The resulting models reproduce reference density and ion-coordination structure, providing a scalable uncertainty-quantification strategy across MLFF training regimes.

Fractional quantum multiferroics, arising from the coupling between fractional quantum ferroelectricity (FQFE) and altermagnetism (AM), provide a promising platform for nonvolatile control of momentum dependent spin splitting in systems with zero net magnetization. However, extending this FQFE-AM coupling to valley degrees of freedom and Berry curvature driven valley Hall effects remains largely unexplored. Here, using first-principles calculations, we demonstrate that monolayer Cr2S2 realizes a two dimensional FQFE-AM platform with two switchable FQFE states connected by composite symmetry operations combining a fractional lattice translation with time reversal or parity-time reversal. We show that FQFE switching reverses the AM spin-polarized band structure and interchanges the spin characters of the X and Y valleys without rotating the Néel vector, thereby enabling polarization switchable spin-valley locking. Moreover, the two FQFE states exhibit reversed Berry curvature distributions, which, together with the switched spin-valley locking, enable polarization controlled valley Hall effects under both electron and hole doping. These results demonstrate a symmetry based mechanism for nonvolatile electrical control of AM spin splitting, spin-valley locking, and valley Hall effects, offering a general route toward low-power valleytronic devices based on FQFE-AM coupling.

Two-dimensional multiferroic materials, which combine magnetic and ferroelectric (FE) orders with strong magnetoelectric coupling, represent ideal platforms for high-density information storage and low-power multistate electronics. However, the intrinsic bistability of conventional ferroelectricity poses a substantial challenge to realizing multiple nonvolatile states and programmable Berry-curvature driven transport responses within a single material. Here, using first-principles calculations, we predict multistate ferroelectricity in AA0-stacked bilayer ReIrGe2Se6. The system hosts four energetically stable FE polarization configurations, among which three are connected through reversible switching pathways, while the fourth exhibits a unidirectional switching pathway. The distinct FE configurations further give rise to a cyclic semiconductor-metal-semiconductor evolution in the electronic structure. Notably, FE polarization switching is intimately coupled to layer degrees of freedom and Berry curvature. The layer-dependent electrostatic potential associated with different FE configurations controls the layer character of the band-edge states, thereby locking the Berry curvature to specific layer channels. As a result, bilayer ReIrGe2Se6 enables switching between an anomalous valley Hall effect and a layer-locked anomalous valley Hall effect, providing nonvolatile control of layer, valley, and spin-resolved transport responses. In addition, magnetization reversal switches the valley and spin channels while preserving the layer-resolved character. These results establish bilayer ReIrGe2Se6 as a multistate ferroelectric platform for programmable Berry-curvature related transport, offering microscopic insight into topology based multifunctional electronic and valleytronic devices.

Altermagnets combine compensated collinear magnetic order with momentum-dependent spin splitting, offering a promising platform for coupling spin and valley degrees of freedom with ferroelectricity and Berry-curvature driven transport in the absence of net magnetization. However, achieving nonvolatile and selective control of these intertwined degrees of freedom remains a key challenge. Here, using first-principles calculations, we show that the direction of interlayer sliding serves as a symmetry selective control parameter in altermagnetic bilayer Fe2WS4. Diagonal sliding breaks inversion symmetry and produces two sliding ferroelectric states with opposite out-of-plane polarizations. Reversal of the ferroelectric polarization switches the momentum-dependent spin texture and reverses the anomalous Hall conductivity, revealing strong magnetoelectric coupling and enabling a ferroelectrically switchable anomalous Hall effect. In contrast, axial sliding preserves inversion symmetry but breaks the crystalline symmetry relating the X and Y valleys, leading to reversible valley polarization and a switchable anomalous valley Hall effect. These results establish the direction of interlayer sliding as a nonvolatile symmetry selector for controlling ferroelectricity, spin texture, valley polarization, and Hall transport responses in two-dimensional altermagnetic bilayers.

Biomolecular condensates are continually remodeled by biochemical reactions that can exhibit non-Markovian, history-dependent dynamics. We develop a theory of active phase separation with non-Markovian reactions and show that delayed reaction feedback destabilizes stationary droplets: when the memory time becomes comparable to the reaction turnover time, condensates deform and spontaneously acquire a polar, self-propelled state. In multidroplet systems, persistent memory wakes mediate alignment, producing polar flocks and, at higher concentrations, traveling labyrinths. These results establish reaction memory as a control parameter of active phase separation, linking condensate remodeling, autonomous motility, and collective organization, and suggest a possible route to flocking-like behavior within cells.

Most networks, from friendships to the internet, break up into communities: groups of nodes more densely connected to one another than to the rest. A basic question has remained open: how many communities should a network have, and how does that number grow with size? Simple models bracket the possibilities. In a small-world network built from dense modules – a caveman graph of cliques – each module is a community, so the number grows in proportion to size, as $n$. In self-similar, fractal networks it grows far more slowly, as the square root. Real networks could lie anywhere between. Here we measure the number of communities across close to a hundred real networks spanning four orders of magnitude, from a $34$-member club to millions of nodes, and within individual systems followed over decades as they grow. We find a power law with an exponent between one half and two thirds – above the fractal value and below the linear limit. Simple models of network growth by local rules reproduce the same super-fractal exponent, a stable and measurable property of network organization. In short, network evolution herds a system's components into clusters, whose number grows as a power law of size.

Chiral superconductivity has recently been confirmed in rhombohedral tetra- and pentalayer graphene near the BCS–BEC crossover, but no theory tells the experimentalist what thermal Hall response to expect, or why any signal should persist above the phase-coherence temperature $T_c$. We show that the parity anomaly of $(2{+}1)$-dimensional field theory fixes the answer exactly, at all temperatures, with no free parameters: $\kappa_{xy}/T = (\pi^2 k_B^2/6h)\,C_{\rm BdG}\,\tanh[\Delta(T)/(2k_BT)]$, where $C_{\rm BdG}$ is the BdG Chern number and $\Delta(T)$ is the fermionic excitation gap. The BCS–BEC two-gap relation $\Delta^2 = \Delta_{\rm sc}^2 + \Delta_{\rm pg}^2$ makes the same formula govern both the condensate and pseudogap regimes, so the signal onsets at the pair-formation temperature $T^{*}$ rather than at $T_c$. Coleman–Hill non-renormalization and the $c_1 = 0$ theorem protect this result against interactions and finite-size artefacts. Three independent numerical validations confirm the topological input at machine precision (FHS Chern numbers, Wilson-loop $c_1 = 0$ test) and at the many-body level (DMRG on 28 converged ground states, including the real-space $p+ip$ signature $\arg\mathcal{A}_y - \arg\mathcal{A}_x = -\pi/2$ recovered to $10^{-14}$). The theory delivers an immediate falsifiable test that requires no new experimental apparatus: the sign of $\kappa_{xy}/T$ below $T_c$ must equal the sign of the anomalous Hall resistance $R_{xy}$ already measured above $T_c$, and four further predictions accessible by dilution-refrigerator nano-calorimetry on existing devices.

I present an overview of different phases used in the literature to describe the phase of travelling waves in reaction-diffusion equations. The discussion is tailored to understand the effectiveness of these different phase descriptions in a stochastic setting in 1D. The explicit computation of the autonomous isochronal phase for the Nagumo equation is a new result.

Quantum Hall scanning images are often read as maps of a local potential, temperature, or viscosity, whereas a probe records a finite-resolution functional of a transport operator. We formulate this functional using Landau-level projection, a particle-number Ward identity, magnetization-subtracted thermoelectric transport, a hydrodynamic Stokes-Ohm inversion, and finite-tip Fisher information. Two results follow in complementary transport regimes. In the strong-field, sharp-Landau-level regime, the defect-induced thermoelectric and electrical Hall contrasts of a smooth scalar defect obey $\delta\alpha_{xy}^{tr}/\delta\sigma_{xy}=(E_c-\mu)/(eT)$. At the retained long-wavelength order, the orbital form factor, defect geometry, and common tip kernel cancel after the heat-magnetization current is removed, so the zero of the thermoelectric contrast is pinned by energy weighting at $E_c=\mu$ rather than by defect shape. In the hydrodynamic regime, the measurable $q^2$ tensor amplitudes mix Hall, longitudinal, transverse, boundary, electrothermal, and kinetic channels, so a Hall-odd image is not by itself a Hall-viscosity measurement. For a representative graphene geometry, a Schur-complement fit against the stated nuisance library yields a conditional one-standard-deviation sensitivity of approximately 68 square nanometers at SNR0 = 200, with boundary slip the limiting nuisance. The framework turns visual interpretation of quantum Hall nanoscopy into a quantitative observability test for electrical, thermoelectric, and viscous response channels.

We report femtosecond time-resolved measurements of confined acoustic phonons in free-standing nanocrystalline silicon membranes and compare them with the crystalline silicon counterpart. While the latter exhibit well-resolved higher-order modes, a strong suppression of these modes is observed in nanocrystalline samples. The suppression is strongly frequency dependent and becomes more pronounced as the phonon wavelength approaches the characteristic grain size. Analysis of the phonon lifetimes reveals an additional frequency-dependent scattering mechanism in nanocrystalline silicon, with a scattering rate that scales approximately as $f^2$, where $f$ is the phonon frequency. The measured sound velocity is consistent with previous reports for nanocrystalline silicon and indicates an effective elastic response arising from multiple crystallographic orientations. These results establish coherent phonons as a sensitive probe of microstructure-dependent scattering in nanocrystalline materials and indicate that grain boundaries act as an effective spectral filter for high-frequency acoustic phonons.

Two-particle coherence is the first level of the reduced-density-matrix hierarchy that contains correlations inaccessible to single-particle observables, yet analytic two-particle density matrices are rare even in one dimension. We derive a closed, finite-size expression for the equal-time two-particle reduced density matrix of spinless fermions in a Tomonaga-Luttinger liquid using constructive bosonization with an explicit ultraviolet cutoff. In addition to the familiar Luttinger parameter $K$-dependent exponent $\gamma^2=(K+K^{-1}-2)/2$ which governs the spatial decay of matrix elements, the result exposes a second exponent, $\lambda=(K^{-1}-K)/2$, which encodes correlations between opposite chiralities and controls the off-diagonal structure. The diagonal limit of the two-particle reduced density matrix yields density correlations and the static structure factor, while its coherences resolve algebraic $2k_F$ charge-density-wave correlations for repulsion and odd-parity p-wave pairing correlations for attraction. After fixing the cutoff from the one-particle density matrix, the analytic result quantitatively reproduces density matrix renormalization group calculations of the interacting J-V chain within the Luttinger liquid regime. The result connects universal Luttinger liquid scaling with observables in finite microscopic systems.

Universality is usually associated with the loss of information about initial conditions under repeated coarse-graining or renormalization-group (RG) transformations. We show that the unified RG framework for nonlinear partial differential equations can accommodate a broader class of asymptotic fixed points in which relevant scales remain encoded in the asymptotic state. By retaining relevant length scales within the RG description, asymptotic self-similar solutions, identified with RG fixed points, become functions of all scales that survive the RG flow. A modified density-dependent diffusion model yields a memory-retaining RG fixed point with scaling form {\eta}^{{\alpha}}F({\xi}/{\eta}^e̱ta}}), where {\eta} represents a surviving relevant scale, while the Barenblatt equation emerges as the special case {\eta}^{{\alpha}}F({\xi}) with e̱ta}=0. These examples suggest that asymptotic RG fixed points may be classified according to whether relevant scales survive repeated RG transformations. We refer to the fixed points retaining such information as memory-retaining fixed points. Within this perspective, anomalous scaling can be interpreted as a manifestation of information retention. The resulting classification distinguishes fixed points according to how initial-condition information survives RG flow and remains encoded in the asymptotic fixed-point function itself. The results suggest that memory retention constitutes an organizing principle of RG fixed points complementary to the conventional classification by universality classes. In contrast with conventional Hamiltonian-based RG, the surviving information appears as an explicit variable of the asymptotic RG fixed-point function itself.

A central question in quantum information theory is the circuit complexity of states arising from standard many-body models. We study this question for quantum $p$-spin glasses, random Hamiltonians whose interactions act on $p$-tuples of qubits through Pauli strings. Anschuetz, Gamarnik, and Kiani (arXiv:2404.07231) showed that the optimum energy is separated from the best energy achievable by product states. This leaves open whether shallow circuits can close the gap, since even depth-one circuits can generate entanglement. We show that the entanglement needed to close the product-state gap cannot be generated at shallow depth. When the average interaction degree grows with $n$, we prove that, for all sufficiently large fixed $p$, any circuit preparing an $n$-qubit state whose normalized energy is within a fixed positive constant of the optimum must have depth $\Omega_p(\log n)$. In the bounded-average-degree regime, we prove a fixed-depth obstruction: for every fixed $D$, a sufficiently large degree prefactor rules out depth-$D$ preparation of near-ground states. Both results hold uniformly over circuits with an arbitrary number of ancilla qubits. Our results give an obstruction in the spirit of the No Low-Energy Trivial States problem of Freedman and Hastings (arXiv:1301.1363), but for random quantum spin glasses rather than code-based Hamiltonians such as those of Anshu, Breuckmann, and Nirkhe (arXiv:2206.13228), whose ground states admit polynomial-size preparation circuits. This setting opens a probabilistic route to NLTS-like questions: we recast state-preparation lower bounds for random quantum Hamiltonians as uniform control of Gaussian processes indexed by shallow circuits.

We study a system of two ferromagnetic one-dimensional Ising chains coupled to a thermal bath, which are driven out of equilibrium by being moved past one another at a constant speed. We show that even at modest speeds, magnetic friction between the two chains significantly increases the ability of the system to order. In particular, at inverse temperature $\beta$, Ising coupling $J$, and sliding speed $v$, the dynamics retains memory of its initial magnetization for a time that increases from $\exp(O(\beta J))$ at $v = 0$ to $\exp(O((\b J)^2v))$ when $v>v_c$, where $v_c$ is a small constant. Magnetic friction thus provides a simple mechanism for parametrically slowing down thermalization in a one-dimensional magnet.

Non-conservative multi-body interactions are typically associated with instabilities and activity in driven, field-mediated systems. Here we show that they can also promote stable static structures. Combining experiments and simulations in a minimal, acoustically levitated three-particle system, we tune the relative strength of conservative and non-conservative contributions to the force field. The conservative component favors a symmetric equilibrium configuration, whereas the non-conservative 3-body contribution selects a flattened isosceles triangle. Our results identify non-conservative multi-body forces as a mechanism for static structure selection in driven-dissipative matter in the absence of an effective-energy landscape.

Current quantum hardware is limited by noise and decoherence, which restrict the depth of unitary circuits that can be implemented with high fidelity. We investigate how the compressibility of time-evolution operators depends on the dynamical regime of the underlying many-body system. As a testbed, we study a one-dimensional Floquet random circuit with a tunable competition between interactions and on-site disorder. Using tensor-network simulations, we characterize operator growth through the operator-entanglement entropy of the Floquet unitary as well as of out-of-time-ordered correlators (OTOCs). We find rapid operator scrambling at weak disorder, while strong disorder leads to slow OTOC-front propagation and logarithmic or near-logarithmic operator-entanglement growth over the accessible time window. We then optimize shallow brickwall circuits to approximate the Floquet evolution and show that strong-disorder circuits can be compressed to substantially smaller depths than weak-disorder circuits at fixed logarithmic fidelity density. These results suggest that localized or slowly scrambling dynamics provide a favorable regime for compressed quantum simulation on noisy devices.

We present autohf, a general, easy-to-use mean-field solver for quantum many-fermion Hamiltonians. It allows the user to bypass the process of deciphering the mean-field form for each many-body Hamiltonian $H$ and thus avoid setting up a tailored program for each $H$. Rather, autohf finds the optimal Slater determinant $|\Psi\rangle$, written in terms of orbital coefficients and subject to symmetry constraints, by directly minimizing the variational energy $\langle H \rangle$. By embracing this variational approach, autohf makes use of the growing power of automatic differentiation and optimization tools developed by the machine learning community.

An important feature of solid-state or cold atom systems in low dimensions is the restricted oscillations of ionic/atomic degrees of freedom in the confining directions, for which the conventional phonon from canonical quantization is not an ideal description. In this work we propose a general recipe to introduce this feature to otherwise unrestricted systems by mapping displacement fields to spin degrees of freedom, dubbed soft-corization. In the strong-confinement limit $S=1/2$, we demonstrate the validity of the approach with a harmonic chain; the results lead to a gapped fermionic model showing the absence of acoustic modes as a signature of the confinement of the entire chain. Despite the non-conserved total particle number in the presence of nearest-neighbor parings, the model holds a coarse-grained $U(1)$ symmetry with conserved polarization charge in the absence of nearest-neighbor hopping. This enables a new transport mechanism via "dimer-tumbling" instead of single-particle hopping. We then introduce a short-range interaction via anharmonicity; for energy scales slightly above the gap, it leads to a (quantum) phase transition to a nonreciprocal state carrying polarization charge current and heat current with spontaneous time reversal symmetry breaking (TRSB) of the type $\hat{T}^2=+1$. The non-reciprocity can be probed by measuring the change of inductance due to gauge fields in and out of the ordered phase.

Circuit quantum electrodynamics embeds Josephson junction qubits within superconducting cavities, and has emerged as a leading approach to quantum computing and quantum simulation. Despite the many permutations of circuit geometry that have been explored, Josephson connectivities have so far been planar, making them effectively low-dimensional. Here we show that a non-planar qubit – a $3\times3$ crossbar Josephson array – gives rise to flux-tunable $\mathbb{Z}_3$ combinatorial gauge symmetry (CGS), potentially enabling spin-liquid behavior when networked into a lattice. The observed excitation spectrum shows excellent agreement with predictions from a neural network trained to generate variational quantum states, demonstrating that we have predictive power over our high-dimensional quantum system. Fine-structure splittings near the CGS point are compatible with weak tunneling or symmetry breaking due to experimental imperfections. We additionally use the superconducting cavity to externally induce symmetry breaking, observing a restoration of symmetry at the CGS point where ground states differ only by a $\mathbb{Z}_3$ phase. This work initiates a general program exploring lattice gauge theories using the toolbox of circuit quantum electrodynamics. More broadly, introducing non-planar Josephson connectivities opens a vast space for experimental and theoretical exploration of structures in almost any imaginable dimensionality and geometry.

Understanding how complex systems transition between order and chaos is a central challenge of nonequilibrium physics. While weak perturbations of classical integrable systems give rise to a mixed phase space of coexisting regular and chaotic trajectories, analogous behavior in interacting quantum many-body systems has remained elusive. Here we develop and experimentally implement a hybrid quantum-classical feedback protocol that autonomously discovers and stabilizes long-lived regular trajectories in a superconducting quantum processor. Each iteration combines short-time quantum evolution with classical optimization that projects the dynamics back onto a low-entanglement variational manifold, effectively distilling coherence from chaotic evolution. The stabilized trajectories reveal a quantum many-body mixed phase space emerging from nonlinear variational dynamics, without a direct analogue in classical or few-body quantum systems. Our results establish a versatile framework for algorithmic discovery and control of coherent dynamics previously inaccessible to experiment.

Magic and entanglement are independent quantum resources, yet their exact relation in many-body dynamics has remained elusive. We uncover two structural principles. First, at any stabilizer state, the curvature of the second stabilizer Rényi entropy under an arbitrary Hermitian generator equals the quantum Fisher information up to a fixed normalization, creating a bidirectional bridge between computational and metrological resources. Second, for commuting Ising evolution on any forest graph, a Clifford pruning circuit yields the full stabilizer-Rényi family at arbitrary size and in any spatial embedding, thereby furnishing a graph-theoretic construction of families with finite magic density and vanishing entanglement density in the thermodynamic limit. We solve two paradigmatic one-dimensional realizations central to quantum simulation – an Ising quench and a kicked Floquet chain – exactly for arbitrary system size and directly in the thermodynamic limit, revealing finite magic density with vanishing entanglement density, distinct magic and entanglement revival periods, and Clifford points with zero magic but finite bipartite entanglement. The same tangent geometry fixes initial growth, perturbative revival lifting, and stability of thermodynamic magic minima. Large-scale Pauli-basis matrix-product-state calculations verify all predictions, and the tangent bridge yields a concrete protocol for detecting magic through established quantum-Fisher-information measurements.

We investigate the interface separating two topologically distinct insulating phases of matter using extensive density-matrix renormalization group calculations to study the triangular-lattice Hofstadter-Hubbard model with a spatially varying interaction strength, chosen to realize both integer quantum Hall and chiral spin liquid states in different spatial regions. We find that the integer quantum Hall-chiral spin liquid interface hosts a spinless charged excitation that is bound to the interface. This mode at the interface is identified through charge and spin pumping, and by direct calculations of low-lying excited states. We also characterize bulk excitations in both phases, finding evidence for fractionalization in the chiral spin liquid and for spin-triplet exciton formation in the integer quantum Hall phase.

We provide quantum Monte Carlo calculations of a two-component Fermi system interacting with an attractive interaction confined in harmonic traps. We investigate the role of the interaction's scattering length and effective range and show its important role in modifying shell effects in the structure of these systems. We show that in the strongly interacting regime, where the scattering length is large, the dominant role to shell effects is due to the effective range. These conclusions are very relevant for nuclear physics, in particular for neutron-rich systems, and open the way to perform new atomic experiments that can help to explain the disappearance of shell-effects in nuclei.

The applications for which quantum computers will clearly outperform classical computers are still being identified and benchmarking such an advantage is challenging. We propose a scalable verification scheme for non-equilibrium quantum simulation based on stabilizer scars, a special class of quantum many-body scars, whose structure ensures both classical simulability and efficient direct fidelity estimation. Assuming a physically motivated error model, we show that the fidelity of quantum simulating these states bounds the fidelity of classically intractable simulations, providing a benchmark for quantum-advantage experiments in non-equilibrium dynamics.

Strained membrane resonators have emerged as a promising platform for optomechanical accelerometry; however, the desired combination of low frequency and high $Q$-mass product requires a rethinking of their dissipation dilution engineering. Applying Bayesian optimization to a Si$_3$N$_4$ membrane, we discover a class of sail-like trampoline resonators in which the frequency is decreased by an order of magnitude while preserving the $Q$-mass product. We demonstrate centimeter-scale sails with kHz frequencies, $Q\sim10^7$ and $Q\times\text{mass}\sim$ 10 g. Vertically integrating a 7 kHz device with a nanoribbon, we realize a monolithic cavity optomechanical accelerometer with a room temperature thermal noise of $40\;\text{n}g_0/\sqrt{\text{Hz}}$, sufficient to resolve $\mu g_0/\sqrt{\text{Hz}}$ ambient vibration over a bandwidth of 4 kHz with a displacement imprecision of $10^{-14}\;\text{m}/\sqrt{\text{Hz}}$. Cryogenic arrays of sail membranes may be attractive for new physics searches and distributed quantum sensing experiments.