Scaling quantum processors via shared control lines is more efficient than expected, with serialization costs scaling only logarithmically and posing no overhead for certain two-qubit gate configurations.

A continuously driven Kerr parametric oscillator simulates a dissipative quantum system with applications to reactions in quantum chemistry.

Noise-aware calibration, logical rotation gates, and quantum error-correction gadgets enable a partially fault-tolerant molecular energy computation on a trapped-ion quantum computer.

Classical simulation of a large class of logical magic state preparation protocols is made scalable and efficient via propagating errors to the end of the circuit.

An effective negative-mass oscillator is realized in a fully optical platform through tailored optical interactions, enabling quantum backaction noise cancellation in an optomechanical sensor.

Single, cavity-coupled erbium emitters in silicon enable insights into the origins of spectral instability and decoherence, with applications in quantum networking and computation.

A proposed five-stage framework outlines the path to useful quantum computing, detailing the scientific milestones required to bridge the gap between theory and real-world utility.

Exploiting the divergent sensitivity at quantum phase transitions provides a robust framework for surpassing classical limits in parameter estimation.

A noise-resilient quantum displacement sensor utilizing stabilized GKP states continuously surpasses the Gaussian limit of displacement sensing to approach sensitivity bounds, unlocking pathways for force sensing and waveform estimation.

Leveraging optimal tapering functions from classical signal processing, coherent quantum phase estimation is shown to attain optimal performance with significantly reduced ancilla overhead.

A new measurement scheme can achieve large reductions in the number of measurements needed for estimation of the energy of quantum lattice models.

The action of a quantum convolutional neural network, which is a promising architecture for quantum machine learning, can be efficiently simulated by a classical computer.

A synthetic time-domain photonic processor exponentially reduces hardware complexity while maintaining all-to-all connectivity, exceeding performance thresholds for scalable, universal quantum computation under realistic physical constraints.

Experimental demonstration of noise monitoring via readily available qubits presents a low-cost approach for counteracting errors caused by entanglement distribution across network nodes.

Entanglement between an electronic spin sensor and a nuclear ancillary spin in experiment allows for concurrent estimation of amplitude, frequency, and phase from a single measurement sequence.

Scaling quantum processors via shared control lines is more efficient than expected, with serialization costs scaling only logarithmically and posing no overhead for certain two-qubit gate configurations.

A continuously driven Kerr parametric oscillator simulates a dissipative quantum system with applications to reactions in quantum chemistry.

Radial codes, a new class of low-density parity-check codes with strong error correction capabilities, tunable parameters, and small size, are shown to be a promising candidate for near-term quantum devices.

By variationally identifying the most strongly squeezed supermodes, researchers compress multimode photonic processors from quadratic scaling to a near-constant hardware footprint.

An information-theoretic analysis of Markovian noise reveals the fundamental limits of data storage and error correction in noisy quantum memories.

Arbitrary local noise makes it easier to predict measurement outcomes of typical quantum circuits on classical computers.

A hardware-friendly quantum thermalization protocol replaces block encoding with local circuits while preserving rapid mixing and accuracy.

By generalizing from qubit error correction, fault-tolerant protocols tailored to fermionic processes are created, which enable gates, measurements, and codes.

A new theoretical framework defines the limits of Gaussian cooling and shows how non-Gaussian resources unlock even colder states for bosonic devices.

Radio-frequency gate reflectometry enables fast, noninvasive readout of coupled quantum dot and superconductor systems, resolving key processes and parity dynamics essential for realizing Majorana-based Kitaev chain qubits.

A quantum filtering algorithm identifies clusters of eigenvalues and their multiplicities, enabling efficient spectral analysis beyond worst-case complexity.

Noise-aware calibration, logical rotation gates, and quantum error-correction gadgets enable a partially fault-tolerant molecular energy computation on a trapped-ion quantum computer.

Combinations of discrete- and continuous-variable systems are brought into the stabilizer formalism with new classes of stabilizer states and scalable error-correcting codes and could improve displacement sensing protocols.

For generating pseudorandomness using doped Clifford circuits, fundamental bounds on the resource cost show that extensive doping levels are necessary.

An approach to probing quantum chaos by repeated interventions is shown to unify techniques for the study and simulation of many-body quantum dynamics.

Using a procedure based on symmetric tensor decomposition, every photonic state can be prepared with realistic experimental tools and a predictable number of steps.

By tuning the pairwise exchange interactions between three exchange-coupled electrons to be exactly equal, an energy gap between the computational subspace and extraneous levels is created, suppressing leakage errors.

Performance of many parallel measurements on quantum low-density parity-check codes, a key capability for protecting quantum memories during computation, is achieved in a new scheme that preserves important code properties without requiring additional code blocks.

A new family of quantum low-density parity-check codes, which are locally equivalent to higher-dimensional hypergraph-product codes, achieves single-shot fault tolerance and an approximately 1.1% pseudothreshold with significantly shorter block lengths.

A comprehensive noise modeling approach for transmon-based quantum processors captures complex spatiotemporally correlated errors, achieving a sevenfold improvement in accuracy when used as a hardware proxy simulator for variational algorithms.

An investigation of Haar-random quantum codes reveals a simple mechanism for the transition between decodable and nondecodable phases of quantum codes under local noise.

Classical simulation of a large class of logical magic state preparation protocols is made scalable and efficient via propagating errors to the end of the circuit.

Adaptive subspace-switching readout improves nondemolition measurements in multilevel quantum systems, boosting qudit readout fidelity to 99.61% while reducing measurement time and mitigating measurement-induced errors across platforms.

New probes of string breaking reveal experimentally accessible regimes in which the confining strings do not simply break but exhibit complex quantum dynamics.

Partially randomized product formulas slash the Hamiltonian simulation overhead in quantum phase estimation, offering orders-of-magnitude resource savings for quantum chemistry benchmarks.

Careful tuning of qubit-coupler interactions and a new calibration protocol enable simultaneous high-fidelity single-qubit gates, controlled-$Z$ gates, and readout in superconducting circuits, advancing scalable quantum computing.

Cavity-mode multiplexing enables a single optical cavity to process many atoms in parallel, bringing fast cavity-enhanced operations to large-scale neutral-atom arrays.

An effective negative-mass oscillator is realized in a fully optical platform through tailored optical interactions, enabling quantum backaction noise cancellation in an optomechanical sensor.

A principled link between noise resilience and circuit expressivity provides a roadmap for navigating barren plateaus and optimizing the training of variational quantum algorithms.

An efficient quantum algorithm solves the Abelian state hidden subgroup problem, unifying key symmetry-learning primitives.

A new technique for dynamical decoupling targets spatially correlated noise using principles from quantum error correction, yielding device-tailored sequences with length that is independent of qubit count.

Integer fluxonium qubits leverage parity symmetry and dispersive readout to convert dominant energy relaxation errors into detectable erasures, significantly boosting effective coherence times.

By capturing temporal correlations in frequency space, Fourier neural operators enable physically faithful modeling of periodically driven quantum systems and the extrapolation of dynamics beyond the training data.

Motivated by recent quantum-dot experiments, this work rigorously defines Majorana bound states in interacting systems to quantify their protection and feasibility for non-Abelian braiding.

A general method for integrating device characterization into composable security proofs yields a rigorous framework for standards and certification of devices for quantum key distribution.

Integration of a space-time efficient small-angle rotation error correction architecture with neutral-atom hardware and its extension to high-rate codes yields significant savings in logical layout, space, and time overhead for quantum simulation.

Impedance-matched nondegenerate Josephson mixers break through traditional performance limits, enabling simultaneous processing of multiple quantum signals in large-scale processors.

By harnessing nontrivial commuting structures in quantum circuits, a novel multiproduct commutation relation significantly reduces the costly $T$-count required for fault-tolerant quantum computation.

Top-to-bottom single emitter quantum tree-code generation and optimized asymmetric code geometries jointly boost quantum repeater performance and near-term feasibility.

Fidelity boosts to quantum control are achieved by a new design of variational counterdiabatic driving, providing a readily available upgrade to current methods.

A deep-level defect in ZnO with an unusually small electron-phonon coupling, a 4-ms spin coherence time, and high spin selectivity for single-shot readout, establishes wide-band-gap oxides as a viable new platform for scalable quantum technologies.

Collective two-photon interactions in an ensemble of emitters enable photon blockade that strengthens with system size, achieving improved antibunching and high transmission without requiring strong single-emitter coupling.

Mapping ancillary degrees of freedom to a one-dimensional tight-binding lattice overcomes traditional connectivity bottlenecks, enabling the near optimal quantum simulation of nonunitary dynamics.

A novel spectroscopy method leverages single-shot readouts to extract noise cross-correlations, successfully bridging the elusive intermediate-frequency gap in qubit noise characterization.

Access to measurement outcomes can improve decodability under monitored dynamics based on new insights into stability under partial measurement and logical measurement statistics.

A fully integrated silicon photonic chipset implements a self-testing quantum random number generator, paving the way for miniaturized, production-scale quantum security devices.

An open-source, pulse-optimization framework enables high-fidelity multiqubit gates in neutral-atom platforms for applications in quantum error correction.

A comprehensive quantum algorithmic pipeline for approximating the Jones polynomial is shown to serve as a benchmark for quantum computers and yield new insights into potential quantum advantage.

Strong and weak symmetry reductions render optimal stabilizer decompositions tractable for multiqubit unitaries beyond previous limits.

A minimal model for cavity-coupled Rydberg arrays reveals how kinetically constrained long-range interactions stabilize exotic phenomena ranging from blockaded superradiance to long-range quantum scars.

Electromagnetically induced transparency unlocks high-fidelity, nondestructive imaging and loading of continuously operated neutral-atom arrays in finite magnetic fields.

Classically surrogating a small subregion of an expectation landscape can be done efficiently, potentially using initial data acquired from quantum computers.

Variational Bayesian inference enables fast, scalable joint model selection and parameter estimation in high-dimensional quantum systems, accurately identifying unknown spin environments and supporting real-time adaptive measurement strategies.

A quantum algorithm achieving exponential speedup for a topological data analysis problem is proposed, potentially driving new practical applications in quantum computing.

A control framework for heterogeneous solid-state spin emitters enables high-fidelity global operations and scalable optically heralded entanglement with $O$(1) experimental overhead across 10–100 qubits.

Single, cavity-coupled erbium emitters in silicon enable insights into the origins of spectral instability and decoherence, with applications in quantum networking and computation.

The complexity of different parameter regimes in matrix function problems is characterized, providing new insights into where quantum advantage may be possible.

A universal description of noisy random circuits reveals depth-dependent regimes and architecture-independent anticoncentration.

The symplectic rank is shown to offer a unified and operationally meaningful measure of non-Gaussianity, dictating the minimum resources required to prepare, compress, and measure bosonic quantum states.

A family of scalable circuits designed for universal quantum computing on planar chips with nearest-neighbor couplings called twisted color circuits is introduced and can achieve fault tolerance with a “just-in-time” decoder.

Spin-dependent squeezed states in trapped-ion platforms enable optimal displacement sensing, advancing precision metrology.

Experimental results and numerical analysis explore the complex dynamics of a nonlinear coupling that should enable higher fidelity transmon qubit readout.

Decomposition of a large class of quantum field dynamics into standard optical elements allows for highly configurable and efficient execution of simulation algorithms.