Tensor network contraction is central to problems ranging from many-body physics to computer science. We describe how to approximate tensor network contraction through bond compression on arbitrary graphs. In particular, we introduce a hyperoptimization over the compression and contraction strategy itself to minimize error and cost. We demonstrate that our protocol outperforms both handcrafted contraction strategies in the literature as well as recently proposed general contraction algorithms on a variety of synthetic and physical problems on regular lattices and random regular graphs. We further showcase the power of the approach by demonstrating approximate contraction of tensor networks for frustrated three-dimensional lattice partition functions, dimer counting on random regular graphs, and to access the hardness transition of random tensor network models, in graphs with many thousands of tensors.

Many organisms exhibit branching morphologies that twist around each other and become entangled. Entanglement occurs when different objects interlock with each other, creating complex and often irreversible configurations. This physical phenomenon is well studied in nonliving materials, such as granular matter, polymers, and wires, where it has been shown that entanglement is highly sensitive to the geometry of the component parts. However, entanglement is not yet well understood in living systems, despite its presence in many organisms. In fact, recent work has shown that entanglement can evolve rapidly and play a crucial role in the evolution of tough, macroscopic multicellular groups. Here, through a combination of experiments, simulations, and numerical analyses, we show that growth generically facilitates entanglement for a broad range of geometries. We find that experimentally grown entangled branches can be difficult or even impossible to disassemble through translation and rotation of rigid components, suggesting that there are many configurations of branches that growth can access that agitation cannot. We use simulations to show that branching trees readily grow into entangled configurations. In contrast to nongrowing entangled materials, these trees entangle for a broad range of branch geometries. We, thus, propose that entanglement via growth is largely insensitive to the geometry of branched trees but, instead, depends sensitively on timescales, ultimately achieving an entangled state once sufficient growth has occurred. We test this hypothesis in experiments with snowflake yeast, a model system of undifferentiated, branched multicellularity, showing that lengthening the time of growth leads to entanglement and that entanglement via growth can occur for a wide range of geometries. Taken together, our work demonstrates that entanglement is more readily achieved in living systems than in their nonliving counterparts, providing a widely accessible and powerful mechanism for the evolution of novel biological material properties.

Owing to their strong dipole moment and long coherence times, superconducting qubits have demonstrated remarkable success in hybrid quantum circuits. However, most qubit architectures are limited to the GHz frequency range, severely constraining the class of systems they can interact with. The fluxonium qubit, on the other hand, can be biased to very low frequency while being manipulated and read out with standard microwave techniques. Here, we design and operate a heavy fluxonium with an unprecedentedly low transition frequency of 1.8 MHz. We demonstrate resolved sideband cooling of the “hot” qubit transition with a final ground state population of 97.7%, corresponding to an effective temperature of $23\mathrm{\mu }\mathrm{K}$. We further demonstrate coherent manipulation with coherence times $T_1=34\mathrm{\mu }\mathrm{s}$, $T_2^{*}=39\mathrm{\mu }\mathrm{s}$, and single-shot readout of the qubit state. Importantly, by directly addressing the qubit transition with a capacitively coupled waveguide, we showcase its high sensitivity to a radio-frequency field. Through cyclic qubit preparation and interrogation, we transform this low-frequency fluxonium qubit into a frequency-resolved charge sensor. This method results in a charge sensitivity of $33\mathrm{\mu }\mathrm{e}/\sqrt{\mathrm{Hz}}$, or an energy sensitivity (in joules per hertz) of $2.8\hslash$. This method rivals state-of-the-art transport-based devices, while maintaining inherent insensitivity to dc-charge noise. The high charge sensitivity combined with large capacitive shunt unlocks new avenues for exploring quantum phenomena in the 1–10 MHz range, such as the strong-coupling regime with a resonant macroscopic mechanical resonator.

The stability of an optical atomic clock is a critical figure of merit for almost all clock applications. To this end, much optical atomic clock research has focused on reducing clock instability by increasing the atom number, lengthening the coherent interrogation times, and introducing entanglement to push beyond the standard quantum limit. In this work, we experimentally demonstrate an alternative approach to reducing clock instability using a phase estimation approach based on individually controlled atomic ensembles in a strontium (Sr) optical lattice clock. We first demonstrate joint Ramsey interrogation of two spatially resolved atom ensembles that are out of phase with respect to each other, which we call “quadrature Ramsey spectroscopy,” resulting in a factor of 1.36(5) reduction in absolute clock instability as measured with interleaved self-comparisons. We then leverage the rich hyperfine structure of ${}^{87}\mathrm{Sr}$ to realize independent coherent control over multiple ensembles with only global laser addressing. Finally, we utilize this independent control over four atom ensembles to implement a form of phase estimation, achieving a factor of greater than 3 enhancement in coherent interrogation time and a factor of 2.08(6) reduction in instability over an otherwise identical single-ensemble clock with the same local oscillator and the same number of atoms. We expect that multiensemble protocols similar to those demonstrated here will result in reduction in the instability of any optical lattice clock with an interrogation time limited by the local oscillator.

The dipolar-octupolar (DO) pyrochlores, $R_2{M}_2{\mathrm{O}}_7$ ($R=\mathrm{Ce},\mathrm{Sm},\mathrm{Nd}$), are key players in the search for realizable novel quantum spin liquid (QSL) states as a large parameter space within the DO pyrochlore phase diagram is theorized to host QSL states of both dipolar and octupolar nature. New single crystals and powders of ${\mathrm{Ce}}_2{\mathrm{Sn}}_2{\mathrm{O}}_7$, synthesized by hydrothermal techniques, present an opportunity for a new characterization of the exchange parameters in ${\mathrm{Ce}}_2{\mathrm{Sn}}_2{\mathrm{O}}_7$ using the near-neighbor $XYZ$ model Hamiltonian associated with DO pyrochlores. Utilizing quantum numerical linked cluster expansion fits to heat capacity and magnetic susceptibility measurements, and classical Monte Carlo calculations to the diffuse neutron diffraction of the new hydrothermally grown ${\mathrm{Ce}}_2{\mathrm{Sn}}_2{\mathrm{O}}_7$ samples, we place ${\mathrm{Ce}}_2{\mathrm{Sn}}_2{\mathrm{O}}_7$’s ground state within the ordered dipolar all-in-all-out (AIAO) Néel phase, with quantum Monte Carlo calculations showing a transition to long-range order at temperatures below those accessed experimentally. Indeed, our new neutron diffraction measurements on the hydrothermally grown ${\mathrm{Ce}}_2{\mathrm{Sn}}_2{\mathrm{O}}_7$ powders show a broad signal at low scattering wave vectors, reminiscent of a dipolar spin ice, in striking contrast from previous powder neutron diffraction on samples grown from solid-state synthesis, which found diffuse scattering at high scattering wave vectors associated with magnetic octupoles and suggested an octupolar quantum spin ice state. We conclude that new hydrothermally grown ${\mathrm{Ce}}_2{\mathrm{Sn}}_2{\mathrm{O}}_7$ samples host a finite-temperature proximate dipolar spin ice phase, above the expected transition to AIAO Néel order.

Moiré materials provide fertile ground for the correlated and topological quantum phenomena. Among them, the quantum anomalous Hall (QAH) effect, in which the Hall resistance is quantized even under zero magnetic field, is a direct manifestation of the intrinsic topological properties of a material and an appealing attribute for low-power electronics applications. The QAH effect has been observed in both graphene and transition metal dichalcogenide (TMD) moiré materials. It is thought to arise from the interaction-driven valley polarization of the narrow moiré bands. Here, we show that the newly discovered QAH state in AB-stacked ${\mathrm{MoTe}}_2/{\mathrm{W}\mathrm{S}\mathrm{e}}_2$ moiré bilayers is not valley polarized but valley coherent. The layer- and helicity-resolved optical spectroscopy measurement reveals that the QAH ground state possesses spontaneous spin (valley) polarization aligned (antialigned) in two TMD layers. In addition, saturation of the out-of-plane spin polarization in both layers occurs only under high magnetic fields, supporting a canted spin texture. Our results call for a new mechanism for the QAH effect and highlight the potential of TMD moiré materials with strong electronic correlations and spin-orbit interactions for exotic topological states.

Exotic quantum many-body states, such as Haldane and spin liquid phases, can exhibit remarkable features like fractional excitations and non-Abelian statistics and offer new understandings of quantum entanglement in many-body quantum systems. These phases are classified by nonlocal correlators that can be directly measured in atomic analog quantum simulating platforms, such as optical lattices and Rydberg atom arrays. However, characterizing these phases in large systems is experimentally challenging because they are sensitive to local errors like atom loss, which suppress its signals exponentially. Additionally, protocols for systematically identifying and mitigating uncorrelated errors in analog quantum simulators are lacking. Here, we address these challenges by developing an error-correction method for large-scale neutral atom quantum simulators using optical lattices. Our error-correction method can distinguish correlated particle-hole pairs from uncorrelated holes in the Mott insulator. After removing the uncorrelated errors, we observe a dramatic improvement in the nonlocal parity correlator and find the perimeter scaling law. Furthermore, the error model provides a statistical estimation of fluctuations in site occupation, from which we measure the generalized brane correlator and confirm that it can be an order parameter for Mott insulators in two dimensions. Our work provides a promising avenue for investigating and characterizing exotic phases of matters in large-scale quantum simulators.

Soap bubbles are simple, yet very unique and marvelous objects. They exhibit a number of interesting properties such as beautiful interference colors and the formation of minimal surfaces. Various optical phenomena have been studied in soap films and bubbles, but so far they have not been employed as optical cavities. Here we demonstrate that dye doped soap or smectic liquid crystal bubbles can support whispering gallery mode lasing, which is observed in the spectrum as hundreds of regularly spaced peaks, resembling a frequency comb. The lasing enabled the measurement of size changes as small as 10 nm in a millimeter-sized, $\sim 100\text{−}\mathrm{nm}$-thick bubble. Bubble lasers were used as extremely sensitive electric field sensors with a smallest measurable electric field of $110{\mathrm{Vm}}^{-1}{\mathrm{Hz}}^{-1/2}$. They also enable the measurement of pressures up to a 100 bar with a resolution of 1.5 Pa, resulting in a dynamic range of almost ${10}^7$. By connecting the bubble to a reservoir of air, almost arbitrarily low pressure changes can be measured while maintaining an outstanding dynamic range. The demonstrated soap bubble lasers are a very unique type of microcavities which are one of the best electric field and pressure microsensors to date and could in the future also be employed to study thin films and cavity optomechanics.

The discrepancies between reality and simulation impede the optimization and scalability of solid-state quantum devices. Disorder induced by the unpredictable distribution of material defects is one of the major contributions to the reality gap. We bridge this gap using physics-aware machine learning, in particular, using an approach combining a physical model, deep learning, Gaussian random field, and Bayesian inference. This approach enables us to infer the disorder potential of a nanoscale electronic device from electron-transport data. This inference is validated by verifying the algorithm’s predictions about the gate-voltage values required for a laterally defined quantum-dot device in AlGaAs/GaAs to produce current features corresponding to a double-quantum-dot regime.

The elementary excitations in weakly interacting quantum fluids have a nontrivial nature which is at the basis of defining quantum phenomena such as superfluidity. These excitations and the physics they lead to have been explored in closed quantum systems at thermal equilibrium both theoretically within the celebrated Bogoliubov framework and experimentally in quantum fluids of ultracold atoms. Over the past decade, the relevance of Bogoliubov excitations has become essential to understand quantum fluids of interacting photons. Their driven-dissipative character leads to distinct properties with respect to their equilibrium counterparts. For instance, the condensate coupling to the photonic vacuum environment leads to a nonzero generation rate of elementary excitations with many striking implications. In this work, considering that quantum fluids of light are often hosted in solid-state systems, we show within a joint theory-experiment analysis that the vibrations of the crystal constitute another environment that the condensate is fundamentally coupled to. This coupling leads to a unique heat transfer mechanism, resulting in a large generation rate of elementary excitations in typical experimental conditions, and to a fundamental nonzero contribution at vanishing temperatures. Our work provides a complete framework for solid-embedded quantum fluids of light, which is invaluable in view of achieving a regime dominated by photon-vacuum fluctuations.

A number of commercially available quantum computers, such as those based on trapped-ion or superconducting qubits, can now perform mid-circuit measurements and resets. In addition to being crucial for quantum error correction, this capability can help reduce the number of qubits needed to execute many types of quantum algorithms by measuring qubits as early as possible, resetting them, and reusing them elsewhere in the circuit. In this work, we introduce the idea of qubit-reuse compilation, which takes as input a quantum circuit and produces as output a compiled circuit that requires fewer qubits to execute due to qubit reuse. We present two algorithms for performing qubit-reuse compilation: an exact constraint programming optimization model and a greedy heuristic. We introduce the concept of dual circuits, obtained by exchanging state preparations with measurements and vice versa and reversing time, and show that optimal qubit-reuse compilation requires the same number of qubits to execute a circuit as its dual. We illustrate the performance of these algorithms on a variety of relevant near-term quantum circuits, such as one-dimensional and two-dimensional time-evolution circuits, and numerically benchmark their performance on the quantum adiabatic optimization algorithm (QAOA) applied to the MaxCut problem on random three-regular graphs. To demonstrate the practical benefit of these techniques, we experimentally realize an 80-qubit QAOA MaxCut circuit on the 20-qubit Quantinuum H1-1 trapped-ion quantum processor using qubit-reuse compilation algorithms.

We calculate quantum corrections to the entropy of four-dimensional de Sitter space induced by higher-derivative terms in the gravitational action and by one-loop effects. Employing the intertwinement in semiclassical gravity of Euclidean de Sitter and anti–de Sitter saddles, we embed effective de Sitter gravity theories in M theory and express the entropy in terms of the regularized Euclidean anti–de Sitter action on an auxiliary ${\mathrm{EAdS}}_4\times S^7/{\mathbb{Z}}_k$ background.We conjecture that the partition function of the holographically dual 3D Aharony-Bergman-Jafferis-Maldacena CFT determines the explicit form of the corrections to the de Sitter entropy. This includes a logarithmic term, the coefficient of which, we show, agrees with an independent one-loop calculation around the $-S^4\times S^7/{\mathbb{Z}}_k$ Euclidean de Sitter saddle. This provides evidence that the microscopic degrees of freedom behind the entropy of four-dimensional de Sitter space in gravitational theories with a holographic dual description are encapsulated by the path integral of the Euclidean CFT on the three-sphere.

After two decades of measurements, neutrino physics is now advancing into the precision era. With the long-baseline experiments designed to tackle current open questions, a new query arises: Can atmospheric neutrino experiments also play a role? To that end, we analyze the expected sensitivity of current and near-future water(ice)-Cherenkov atmospheric neutrino experiments in the context of standard three-flavor neutrino oscillations. In this first in-depth combined atmospheric neutrino analysis, we analyze the current shared systematic uncertainties arising from the common flux and neutrino-water interactions. We then implement the systematic uncertainties of each experiment in detail and develop the atmospheric neutrino simulations for Super-Kamiokande, with and without neutron-tagging capabilities, IceCube Upgrade, ORCA, and Hyper-Kamiokande detectors. We carefully review the synergies and features of these experiments to examine the potential of a joint analysis of these atmospheric neutrino data in resolving the ${\theta }_{23}$ octant at 99% confidence level (CL), and determining the neutrino mass ordering above $5\sigma$ by 2030. Additionally, we assess the capability to constrain ${\theta }_{13}$ and the $CP$-violating phase (${\delta }_{CP}$) in the leptonic sector independently from reactor and accelerator neutrino data. A combination of the atmospheric neutrino measurements will enhance the sensitivity to a greater extent than the simple sum of individual experiment results reaching more than $3\sigma$ for some values of ${\delta }_{CP}$. These results will provide vital information for next-generation accelerator neutrino oscillation experiments such as DUNE and Hyper-Kamiokande.

Individuals involved in common group activities or settings, e.g., college students that are enrolled in the same class and/or live in the same dorm, are exposed to recurrent contacts of physical proximity. These contacts are known to mediate the spread of an infectious disease; however, it is not obvious how the properties of the spreading process are determined by the structure of and the interrelation among the group settings that are at the root of those recurrent interactions. Here, we show that reshaping the organization of groups within a population can be used as an effective strategy to decrease the severity of an epidemic. Specifically, we show that when group structures are sufficiently correlated, e.g., the likelihood for two students living in the same dorm to attend the same class is sufficiently high, outbreaks are longer but milder than for uncorrelated group structures. Also, we show that the effectiveness of interventions for disease containment increases as the correlation among group structures increases. We demonstrate the practical relevance of our findings by taking advantage of data about housing and attendance of students at the Indiana University campus in Bloomington. By appropriately optimizing the assignment of students to dorms based on their enrollment, we are able to observe a twofold to fivefold reduction in the severity of simulated epidemic processes.

Large interacting systems in biology often exhibit emergent dynamics, such as coexistence of multiple timescales, manifested by fat tails in the distribution of waiting times. While existing tools in statistical inference, such as maximum entropy models, reproduce the empirical steady-state distributions, it remains challenging to learn dynamical models. We present a novel inference method, called generalized Glauber dynamics. Constructed through a non-Markovian fluctuation dissipation theorem, generalized Glauber dynamics tunes the dynamics of an interacting system, while keeping the steady-state distribution fixed. We motivate the need for the method on real data from Eco-HAB, an automated habitat for testing behavior in groups of mice under seminaturalistic conditions, and present it on simple Ising spin systems. We show its applicability for experimental data by inferring dynamical models of social interactions in a group of mice that reproduce both its collective behavior and the long tails observed in individual dynamics.

We describe and benchmark a new quantum charge-coupled device (QCCD) trapped-ion quantum computer based on a linear trap with periodic boundary conditions, which resembles a race track. The new system successfully incorporates several technologies crucial to future scalability—including electrode broadcasting, multilayer rf routing, and magneto-optical trap (MOT) loading—while maintaining, and in some cases exceeding, the gate fidelities of previous QCCD systems. The system is initially operated with 32 qubits, but future upgrades will allow for more. We benchmark the performance of primitive operations, including an average state preparation and measurement error of $1.6(1)\times {10}^{-3}$, an average single-qubit gate infidelity of $2.5(3)\times {10}^{-5}$, and an average two-qubit gate infidelity of $1.84(5)\times {10}^{-3}$. The system-level performance of the quantum processor is assessed with mirror benchmarking, linear cross-entropy benchmarking, a quantum volume measurement of $\mathrm{QV}=2^{16}$, and the creation of 32-qubit entanglement in a GHZ state. We also tested application benchmarks, including Hamiltonian simulation, QAOA, error correction on a repetition code, and dynamics simulations using qubit reuse. We also discuss future upgrades to the new system aimed at adding more qubits and capabilities.

We demonstrate midcircuit measurements in a neutral atom array by shelving data qubits in protected hyperfine-Zeeman substates while nondestructively measuring an ancilla qubit. Measurement fidelity is enhanced using microwave repumping of the ancilla during the measurement. The coherence of the shelved data qubits is extended during the ancilla readout with dynamical decoupling pulses, after which the data qubits are returned to $m_f=0$ computational basis states. We demonstrate that the quantum state of the data qubits is well preserved up to a constant phase shift with a state preparation and measurement–corrected process fidelity of $\mathcal{F}=97.0(5)\%$. The measurement fidelities on the ancilla qubit after correction for state preparation errors are $\mathcal{F}=94.9(8)\%$ and $\mathcal{F}=95.3(1.1)\%$ for $|0⟩$ and $|1⟩$ qubit states, respectively. We discuss extending this technique to repetitive quantum error correction using quadrupole recooling and microwave-based quantum-state resetting.

Quantifying electron-phonon interactions for the surface states of topological materials can provide key insights into surface-state transport, topological superconductivity, and potentially how to manipulate the surface state using a structural degree of freedom. We perform time-resolved x-ray diffraction (XRD) and angle-resolved photoemission (ARPES) measurements on ${\mathrm{Bi}}_2{\mathrm{Te}}_3$ and ${\mathrm{Bi}}_2{\mathrm{Se}}_3$, following the excitation of coherent $A_{1g}$ optical phonons. We extract and compare the deformation potentials coupling the surface electronic states to local $A_{1g}$-like displacements in these two materials using the experimentally determined atomic displacements from XRD and electron band shifts from ARPES. We find the coupling in ${\mathrm{Bi}}_2{\mathrm{Te}}_3$ and ${\mathrm{Bi}}_2{\mathrm{Se}}_3$ to be similar and in general in agreement with expectations from density functional theory. We establish a methodology that quantifies the mode-specific electron-phonon coupling experimentally, allowing detailed comparison to theory. Our results shed light on fundamental processes in topological insulators involving electron-phonon coupling.

The Mott insulator provides an excellent foundation for exploring a wide range of strongly correlated physical phenomena, such as high-temperature superconductivity, quantum spin liquid, and colossal magnetoresistance. A Mott insulator with the simplest degree of freedom is an ideal and highly desirable system for studying the fundamental physics of Mottness. In this study, we have unambiguously identified such an anticipated Mott insulator in a van der Waals layered compound ${\mathrm{Nb}}_3{\mathrm{Cl}}_8$. In the high-temperature phase, where interlayer coupling is negligible, density functional theory calculations for the monolayer of ${\mathrm{Nb}}_3{\mathrm{Cl}}_8$ suggest a half-filled flat band at the Fermi level, whereas angle-resolved photoemission spectroscopy experiments observe a large gap. This observation is perfectly reproduced by dynamical mean-field theory calculations considering strong electron correlations, indicating a correlation-driven Mott insulator state. Since this half-filled band derived from a single $2a_1$ orbital is isolated from all other bands, the monolayer of ${\mathrm{Nb}}_3{\mathrm{Cl}}_8$ is an ideal realization of the celebrated single-band Hubbard model. Upon decreasing the temperature, the bulk system undergoes a phase transition, where structural changes significantly enhance the interlayer coupling. This results in a bonding-antibonding splitting in the Hubbard bands, while the Mott gap remains dominant. Our discovery provides a simple and seminal model system for investigating Mott physics and other emerging correlated states.

Detection and parameter inference of gravitational-wave signals from compact mergers rely on the comparison of the incoming detector strain data $d(t)$ to waveform templates for the gravitational-wave strain $h(t)$ that ultimately rely on the resolution of Einstein’s equations via numerical relativity simulations. These, however, commonly output a quantity known as the Newman-Penrose scalar ${\psi }_4(t)$ which, under the Bondi gauge, is related to the gravitational-wave strain by ${\psi }_4(t)={\mathit{d}}^{2}h(t)/\mathit{d}{t}^2$. Therefore, obtaining strain templates involves an integration process that introduces artifacts that need to be treated in a rather manual way. By taking second-order finite differences on the detector data and inferring the corresponding background noise distribution, we develop a framework to perform gravitational-wave data analysis directly using ${\psi }_4(t)$ templates. We first demonstrate this formalism, and the impact of integration artifacts in strain templates, through the recovery of numerically simulated signals from head-on collisions of Proca stars injected in Advanced LIGO noise. Next, we reanalyze the event GW190521 under the hypothesis of a Proca-star merger, obtaining results equivalent to those previously published [Phys. Rev. Lett. 126, 081101 (2021)], where we used the classical strain framework. We find, however, that integration errors would strongly impact our analysis if GW190521 was 4 times louder. Finally, we show that our framework fixes significant biases in the interpretation of the high-mass gravitational-wave trigger S200114f arising from the usage of strain templates. We remove the need to obtain strain waveforms from numerical relativity simulations, avoiding the associated systematic errors.