Through atomic-loss spectroscopy the excited-state tune-out wavelength in Yb is found, enabling future applications that require control of atoms in either the ground or clock states.

A six-qubit quantum circuit is executed on a silicon spin-qubit array, marking the largest multiqubit algorithm demonstrated in semiconductor quantum-dot hardware.

A novel connection between quantum error correction and quantum contextuality establishes contextuality as a property of fault-tolerant codes and a resource for scalable quantum computation, resulting in possible routes to improve error correction.

Modeling quantum supervised learning as thermodynamic cooling lets a refrigerator protocol boost sampling efficiency and cut overhead, avoiding complex algorithms like Grover iterations.

By violating a Bell-like inequality with a quantum switch, this experiment verifies indefinite causal order, meaning events can occur in a superposition of temporal sequences.

A pedagogical guide to hybrid qubit-oscillator processors unlocks their potential as a powerful new paradigm in quantum computing.

A new family of codes (ZSZ codes) is introduced, with potential for scalable self-correction and a realistic hardware implementation.

A framework for the quantification of non-Gaussian resources needed for universal quantum computation in many-body quantum systems is introduced and applied to study the growth of non-Gaussianity.

Through atomic-loss spectroscopy the excited-state tune-out wavelength in Yb is found, enabling future applications that require control of atoms in either the ground or clock states.

A comprehensive analysis of fluctuations in open quantum systems using two complementary approaches provides new insights into nonequilibrium dynamics and novel techniques for probing these fluctuations in experiments.

Combining concepts from gate set tomography and Pauli noise learning yields a new protocol for noise characterization that is self-consistent and experimentally practical.

Protected qubits can now support protected gates without prohibitive slowdowns.

The dynamics of a Bose gas in a one-dimensional optical potential are studied in a parameter regime where the tight binding approximation is not valid, revealing new features.

A six-qubit quantum circuit is executed on a silicon spin-qubit array, marking the largest multiqubit algorithm demonstrated in semiconductor quantum-dot hardware.

Phase-space representations are used to characterize how the nonclassicality of a pure target state governs the difficulty of estimating its similarity to an unknown quantum state, both for qubits and continuous variable quantum systems.

Tight lower bounds on entanglement flow through vertex-limited architectures are established, demonstrating that constrained intermediate regions sharply limit bipartite entanglement growth and force slow quantum routing.

A correspondence between quantum states and stochastic processes enables an efficient protocol for generating highly entangled many-body quantum states with finely tunable entanglement.

As models built from quantum kernel methods grow larger, they reach a new regime where performance improves, showcasing “double descent” behavior also known to occur in classical machine learning.

A quantum spin Hall superconducting system where Majorana Kramers pairs can possibly emerge without magnetic fields is established, opening a promising path toward scalable fault-tolerant topological quantum computing.

Randomized measurements enable near-optimal estimation of multiple quantum parameters, providing a powerful and practical route to quantum metrology.

A nonlocal magic state cultivation scheme is implemented on the rotated surface code, promising high-fidelity logical T state preparation without magic state distillation.

Preparing quantum resource states probabilistically via phonons and then converting the states into photons on demand efficiently achieves high fidelities.

Development and demonstration of a probabilistic readout error mitigation scheme for efficient recovery of computational results on circuits containing noisy mid-circuit measurements and feedforward.

Quantum processing of coherently encoded light leads to orders-of-magnitude improvements in imaging performance, including enhanced signals for exoplanet detection.

A novel connection between quantum error correction and quantum contextuality establishes contextuality as a property of fault-tolerant codes and a resource for scalable quantum computation, resulting in possible routes to improve error correction.

A scalable decoding protocol enables fast logic with AMO qubits.

A large-scale coplanar waveguide array is combined with multiple transmon qubits in experiment, achieving new geometries of qubit-qubit interactions and generalizing readout and diagnostics to highly multimode settings.

A driving scheme is introduced, achieving exponential gains in annealing efficiency at the cost of an exponentially small nonlocal correction near the critical point.

A method to characterize an array of sequentially entangled qubits is proposed and used to find the density matrix of a 35-qubit microwave cluster state, paving the way for efficient benchmarking and troubleshooting of entangled photon generation.

A universal, low-overhead adapter enables sparse, fault-tolerant joint logical measurements and gates across arbitrary quantum LDPC codes, with qubit and check costs scaling only linearly (up to polylog factors) in code distance.

A novel optical method is proposed to detect fractionally charged quasiholes in topologically ordered states via formation and observation of anyon-trions—bound states between interlayer excitons and quasiholes—in TMD-graphene heterostructures.

An intuitive framework showing how atomic motion affects photon-mediated qubit entanglement enables the removal of thermal-motion overheads, boosting entanglement rates and fidelities in quantum network links.

By encoding three distinct qubits within each individual ytterbium-171 atom, researchers have unlocked a resource-efficient path to simulating complex nuclear matter on neutral-atom quantum processors.

A multi-observable dynamic mode decomposition approach is shown to extract the ground- and excited-state properties of many-body systems with reduced resource requirements while maintaining accuracy.

Analyzing the quantum mean-value problem in adaptive bosonic circuits proves that regimes with limited adaptive measurements admit efficient classical simulation, even in the presence of non-Gaussian resources.

Experimental demonstration of cluster states enabled with photon-loss detection achieves improved fidelities and persistent entanglement over long chains of qubits, showing promise for building high-complexity states in the microwave domain.

Nearly optimal approximate quantum error correction with high encoding rates and strong noise robustness is proven to be achievable by one-dimensional local random Clifford circuits of only logarithmic depth.

Using percolation-inspired observables accessible to quantum simulators, independent confinement of e- and m-anyons in toric codes on non-square lattices is revealed, exposing a sharp distinction between topological order and deconfinement even at zero temperature.

Environmental synthetic non-Abelian gauge fields redefine quantum light-matter interactions through spin-orbit coupling, dressed and squeezed polaritons, and nonsymmorphic symmetry, enabling the engineering of topological photonic states to drive the development of chiral quantum networks.

A hybrid quantum-classical algorithm enables arbitrary expectation value estimation with exponential error suppression using only a single copy of the quantum state.

A new decoding method focuses on logical observables.

Two-dimensional shuttling could lead to improvements in shuttling fidelity that can enable scalable architectures for quantum dots with long-range connectivity.

Counterdiabatic driving applied to a dissipative superconducting qubit overcomes the breakdown of adiabaticity caused by gain-loss imbalances, enabling the exploration of topological features around exceptional points in non-Hermitian systems.

By combining quantum circuits with neural generative models, efficient and scalable quantum-enhanced sampling becomes feasible without precise circuit optimization.

Qubit shuttling may enable a scalable, fault-tolerant semiconductor spin-qubit architecture with all-to-all logical level connectivity.

The display of memory effects in quantum dynamics is shown to depend on whether it is the quantum state or observable that is evolved.

Improved error-correcting codes and logical gates with promising characteristics are constructed and proven to be interconvertible among three relevant state spaces.

A beam-shaping approach enables efficient light coupling to 2D atomic tweezer arrays by matching their diffraction patterns, with interface efficiency scaling favorably with atom number and robustness to imperfections.

Fault-tolerant simulation of scalar field theory is improved using a finite-volume approach for computing scattering processes, and its potential for practical implementation is explored.

Approximate $k$-designs can be generated from shallow circuits with limited magic gates as a new efficient and realistic approach to random unitaries.

Adaptation of classical phase-retrieval yields a method for quantum phase estimation that enables simpler implementations with reduced gate count, especially under connectivity constraints, and resilience to shot noise.

Frequency-resolved photon detection can unlock hidden information in the light emitted by open quantum systems, enabling metrology that approaches fundamental limits using standard laboratory tools.

Fundamental limits of adaptive measurement in quantum many-body systems are established, showing when logarithmic-sample prediction fails and how optimal algorithms can still be achieved.

A zigzag qubit configuration that enables noise-resilient state transfer and entanglement generation between distant qubits is analyzed and demonstrated on a superconducting quantum processor.

Time-energy uncertainty relations are used to provide a semi-device-independent protocol for randomness certification.

Modeling quantum supervised learning as thermodynamic cooling lets a refrigerator protocol boost sampling efficiency and cut overhead, avoiding complex algorithms like Grover iterations.

Causal inference techniques for characterizing latent variable models are generalized to characterize the quantum states compatible with some quantum network structure.

Generalization of compact localized states to many-body systems with kinetic constraints and chiral symmetry reveals a new type of nonergodic eigenstate.

By implementing transversal gates directly on surface codes in systems with nonlocal connectivity, new cultivation protocols increase magic-state-generation rates by over a factor of 20 and achieve ultralow error rates.

By violating a Bell-like inequality with a quantum switch, this experiment verifies indefinite causal order, meaning events can occur in a superposition of temporal sequences.

A new approach to quantum state tomography, suitable for platforms where local control is difficult, can reconstruct quantum states with high accuracy and efficiency.

Techniques are introduced to verify the dimensionality of entanglement based on the moments of a reduction of a given quantum state, which can be estimated with randomized measurements.

Coupling a fluxonium control qubit to superconducting cavities suppresses detrimental inherited errors and nonlinearities, providing a robust alternative to transmon-based architectures for quantum computation.

Squeezed light sharpens the learning curve for continuous-variable quantum compilers, delivering significant gains in both precision and computational speed.

Flux-tunable superconducting resonators induce controllable nonlinearity in a surface acoustic wave cavity, achieving cross-Kerr interactions between seven pairs of mechanical modes.

A measurement protocol for estimating second-order nonlinear expectation values of quantum observables is introduced and shown to perform optimally in practically relevant contexts.

By leveraging symmetry gauging to transition quantum codes into non-Abelian topological phases, this work enables the implementation of non-Clifford gates essential for universal quantum computing.

A framework utilizing topological quantum field theories and invertible subalgebras realizes all Clifford quantum cellular automata across all spatial dimensions, uncovering dimensional periodicity aligning with algebraic $L$-theory.