As in conventional computing, memories for quantum information benefit from high storage density and, crucially, random access, or the ability to read from or write to an arbitrarily chosen register. However, achieving such random access with quantum memories in a dense, hardware-efficient manner remains a challenge. Here we introduce a protocol using chirped pulses to encode qubits within an ensemble of quantum two-level systems, offering both random access and naturally supporting dynamical decoupling to enhance the memory lifetime. We demonstrate the protocol in the microwave regime using donor spins in silicon coupled to a superconducting cavity, storing up to four weak, coherent microwave pulses in distinct memory modes and retrieving them on demand up to 2 ms later. This approach offers the potential for microwave random access quantum memories with lifetimes exceeding seconds, while the chirped pulse phase encoding could also be applied in the optical regime to enhance quantum repeaters and networks.

We present a novel framework for the equation of state of dense and hot quantum chromodynamics (QCD), which focuses on the region of the phase diagram relevant for neutron star mergers and core-collapse supernovae. The model combines predictions from the gauge/gravity duality with input from lattice field theory, QCD perturbation theory, chiral effective theory, and statistical modeling. It is therefore, by construction, in good agreement with theoretical constraints both at low and high densities and temperatures. The main ingredients of our setup are the nonperturbative V-QCD model based on the gauge/gravity duality, a van der Waals model for nucleon liquid, and the DD2 version of the Hempel-Schaffner-Bielich statistical model of nuclear matter. By consistently combining these models, we also obtain a description for the nuclear to quark matter phase transition and its critical end point. The parameter dependence of the model is represented by three (soft, intermediate, and stiff) variants of the equation of state, all of which agree with observational constraints from neutron stars and their mergers. We discuss resulting constraints for the equation of state, predictions for neutron stars, and the location of the critical point.

The realization of a scalable architecture for quantum information processing is a major challenge for quantum science. A promising approach is based on emitters in nanostructures that are coupled by light. Here, we show that erbium dopants can be reproducibly integrated at well-defined lattice sites by implantation into pure silicon. We thus achieve a narrow inhomogeneous broadening, less than 1 GHz, strong optical transitions, and an outstanding optical coherence even at temperatures of 8 K, with an upper bound to the homogeneous linewidth of around 10 kHz. Our study thus introduces a promising materials platform for the implementation of on-chip quantum memories, microwave-to-optical conversion, and distributed quantum information processing.

Relativity opens the door to a counterintuitive fact: A state can be stable to perturbations in one frame of reference and unstable in another one. For this reason, the job of testing the stability of states that are not Lorentz invariant can be very cumbersome. We show that two observers can disagree on whether a state is stable or unstable only if the perturbations can exit the light cone. Furthermore, we show that, if a perturbation exits the light cone and its intensity changes with time due to dissipation, then there are always two observers that disagree on the stability of the state. Hence, “stability” is a Lorentz-invariant property of dissipative theories if and only if the principle of causality is respected. We present 14 applications to physical problems from all areas of relativistic physics ranging from theory to simulation.

Interfacing electrons and light enables ultrafast electron microscopy and quantum control of electrons, as well as new optical elements for high-sensitivity imaging. Here, we demonstrate for the first time programmable transverse electron-beam shaping in free space based on ponderomotive potentials from short intense laser pulses. We can realize both convex and concave electron lenses with a focal length of a few millimeters, comparable to those in state-of-the-art electron microscopes. We further show that we can realize almost arbitrary deflection patterns by shaping the ponderomotive potentials using a spatial light modulator. Our modulator is lossless and programmable, has unity fill factor, and could pave the way to electron wave-front shaping with hundreds of individually addressable pixels.

Recent series of theoretical and experimental reports have driven attention to time-reversal symmetry-breaking spintronic and spin-splitting phenomena in materials with collinear-compensated magnetic order incompatible with conventional ferromagnetism or antiferromagnetism. Here we employ an approach based on nonrelativistic spin-symmetry groups that resolves the conflicting notions of unconventional ferromagnetism or antiferromagnetism by delimiting a third basic collinear magnetic phase. We derive that all materials hosting this collinear-compensated magnetic phase are characterized by crystal-rotation symmetries connecting opposite-spin sublattices separated in the real space and opposite-spin electronic states separated in the momentum space. We describe prominent extraordinary characteristics of the phase, including the alternating spin-splitting sign and broken time-reversal symmetry in the nonrelativistic band structure, the planar or bulk $d$-, $g$-, or $i$-wave symmetry of the spin-dependent Fermi surfaces, spin-degenerate nodal lines and surfaces, band anisotropy of individual spin channels, and spin-split general, as well as time-reversal invariant momenta. Guided by the spin-symmetry principles, we discover in ab initio calculations outlier materials with an extraordinary nonrelativistic spin splitting, whose eV-scale and momentum dependence are determined by the crystal potential of the nonmagnetic phase. This spin-splitting mechanism is distinct from conventional relativistic spin-orbit coupling and ferromagnetic exchange, as well as from the previously considered anisotropic exchange mechanism in compensated magnets. Our results, combined with our identification of material candidates for the phase ranging from insulators and metals to a parent crystal of cuprate superconductors, underpin research of novel quantum phenomena and spintronic functionalities in high-temperature magnets with light elements, vanishing net magnetization, and strong spin coherence. In the discussion, we argue that the conflicting notions of unconventional ferromagnetism or antiferromagnetism, on the one hand, and our symmetry-based delimitation of the third phase, on the other hand, favor a distinct term referring to the phase. The alternating spin polarizations in both the real-space crystal structure and the momentum-space band structure characteristic of this unconventional magnetic phase suggest a term altermagnetism. We point out that $d$-wave altermagnetism represents a realization of the long-sought-after counterpart in magnetism of the unconventional $d$-wave superconductivity.

Cell migration in confining physiological environments relies on the concerted dynamics of several cellular components, including protrusions, adhesions with the environment, and the cell nucleus. However, it remains poorly understood how the dynamic interplay of these components and the cell polarity determine the emergent migration behavior at the cellular scale. Here, we combine data-driven inference with a mechanistic bottom-up approach to develop a model for protrusion and polarity dynamics in confined cell migration, revealing how the cellular dynamics adapt to confining geometries. Specifically, we use experimental data of joint protrusion-nucleus migration trajectories of cells on confining micropatterns to systematically determine a mechanistic model linking the stochastic dynamics of cell polarity, protrusions, and nucleus. This model indicates that the cellular dynamics adapt to confining constrictions through a switch in the polarity dynamics from a negative to a positive self-reinforcing feedback loop. Our model further reveals how this feedback loop leads to stereotypical cycles of protrusion-nucleus dynamics that drive the migration of the cell through constrictions. These cycles are disrupted upon perturbation of cytoskeletal components, indicating that the positive feedback is controlled by cellular migration mechanisms. Our data-driven theoretical approach therefore identifies polarity feedback adaptation as a key mechanism in confined cell migration.

Biological evolution of a population is governed by the fitness landscape, which is a map from genotype to fitness. However, a fitness landscape depends on the organism’s environment, and evolution in changing environments is still poorly understood. We study a particular model of antibiotic resistance evolution in bacteria where the antibiotic concentration is an environmental parameter and the fitness landscapes incorporate trade-offs between adaptation to low and high antibiotic concentration. With evolutionary dynamics that follow fitness gradients, the evolution of the system under slowly changing antibiotic concentration resembles the athermal dynamics of disordered physical systems under external drives. Exploiting this resemblance, we show that our model can be described as a system with interacting hysteretic elements. As in the case of the driven disordered systems, adaptive evolution under antibiotic concentration cycling is found to exhibit hysteresis loops and memory formation. We derive a number of analytical results for quasistatic concentration changes. We also perform numerical simulations to study how these effects are modified under driving protocols in which the concentration is changed in discrete steps. Our approach provides a general framework for studying motifs of evolutionary dynamics in biological systems in a changing environment.

The synthesis of single-cycle pulses of compressed light and microwave signals sparked novel areas of fundamental research. In the field of acoustics, however, such a generation has not been introduced yet. For numerous applications, the large spatial extent of surface acoustic waves (SAW) causes unwanted perturbations and limits the accuracy of physical manipulations. Particularly, this restriction applies to SAW-driven quantum experiments with single flying electrons, where extra modulation renders the exact position of the transported electron ambiguous and leads to undesired spin mixing. Here, we address this challenge by demonstrating single-shot chirp synthesis of a strongly compressed acoustic pulse. Employing this solitary SAW pulse to transport a single electron between distant quantum dots with an efficiency exceeding 99%, we show that chirp synthesis is competitive with regular transduction approaches. Performing a time-resolved investigation of the SAW-driven sending process, we outline the potential of the chirped SAW pulse to synchronize single-electron transport from many quantum-dot sources. By superimposing multiple pulses, we further point out the capability of chirp synthesis to generate arbitrary acoustic waveforms tailorable to a variety of (opto)nanomechanical applications. Our results shift the paradigm of compressed pulses to the field of acoustic phonons and pave the way for a SAW-driven platform of single-electron transport that is precise, synchronized, and scalable.

We report on a universal method to measure the genuine indistinguishability of $n$ photons—a crucial parameter that determines the accuracy of optical quantum computing. Our approach relies on a low-depth cyclic multiport interferometer with $N=2n$ modes, leading to a quantum interference fringe whose visibility is a direct measurement of the genuine $n$-photon indistinguishability. We experimentally demonstrate this technique for an eight-mode integrated interferometer fabricated using femtosecond laser micromachining and four photons from a quantum dot single-photon source. We measure a four-photon indistinguishability up to $0.81\pm 0.03$. This value decreases as we intentionally alter the photon pairwise indistinguishability. The low-depth and low-loss multiport interferometer design provides an original path to evaluate the genuine indistinguishability of resource states of increasing photon number.

In classical cosmological analysis of large-scale structure surveys with two-point functions, the parameter measurement precision is limited by several key degeneracies within the cosmology and astrophysics sectors. For cosmic shear, clustering amplitude ${\sigma }_8$ and matter density ${\mathrm{\Omega }}_m$ roughly follow the $S_8={\sigma }_8({\mathrm{\Omega }}_m/0.3{)}^{0.5}$ relation. In turn, $S_8$ is highly correlated with the intrinsic galaxy alignment amplitude $A_{\mathrm{IA}}$. For galaxy clustering, the bias $b_g$ is degenerate with both ${\sigma }_8$ and ${\mathrm{\Omega }}_m$, as well as the stochasticity $r_g$. Moreover, the redshift evolution of intrinsic alignment (IA) and bias can cause further parameter confusion. A tomographic two-point probe combination can partially lift these degeneracies. In this work we demonstrate that a deep-learning analysis of combined probes of weak gravitational lensing and galaxy clustering, which we call DeepLSS, can effectively break these degeneracies and yield significantly more precise constraints on ${\sigma }_8$, ${\mathrm{\Omega }}_m$, $A_{\mathrm{IA}}$, $b_g$, $r_g$, and IA redshift evolution parameter ${\eta }_{\mathrm{IA}}$. In a simulated forecast for a stage-III survey, we find that the most significant gains are in the IA sector: the precision of $A_{\mathrm{IA}}$ is increased by approximately 8 times and is almost perfectly decorrelated from $S_8$. Galaxy bias $b_g$ is improved by 1.5 times, stochasticity $r_g$ by 3 times, and the redshift evolution ${\eta }_{\mathrm{IA}}$ and ${\eta }_b$ by 1.6 times. Breaking these degeneracies leads to a significant gain in constraining power for ${\sigma }_8$ and ${\mathrm{\Omega }}_m$, with the figure of merit improved by 15 times. We give an intuitive explanation for the origin of this information gain using sensitivity maps. These results indicate that the fully numerical, map-based forward-modeling approach to cosmological inference with machine learning may play an important role in upcoming large-scale structure surveys. We discuss perspectives and challenges in its practical deployment for a full survey analysis.

Optically addressable spins are a promising platform for quantum information science due to their combination of a long-lived qubit with a spin-optical interface for external qubit control and readout. The ability to chemically synthesize such systems—to generate optically addressable molecular spins—offers a modular qubit architecture which can be transported across different environments and atomistically tailored for targeted applications through bottom-up design and synthesis. Here, we demonstrate how the spin coherence in such optically addressable molecular qubits can be controlled through engineering their host environment. By inserting chromium (IV)-based molecular qubits into a nonisostructural host matrix, we generate noise-insensitive clock transitions, through a transverse zero-field splitting, that are not present when using an isostructural host. This host-matrix engineering leads to spin-coherence times of more than $10\mu \mathrm{s}$ for optically addressable molecular spin qubits in a nuclear and electron-spin-rich environment. We model the dependence of spin coherence on transverse zero-field splitting from first principles and experimentally verify the theoretical predictions with four distinct molecular systems. Finally, we explore how to further enhance optical-spin interfaces in molecular qubits by investigating the key parameters of optical linewidth and spin-lattice relaxation time. Our results demonstrate the ability to test qubit structure-function relationships through a tunable molecular platform and highlight opportunities for using molecular qubits for nanoscale quantum sensing in noisy environments.

For the brain to recognize local orientations within images, neurons must spontaneously break the translation and rotation symmetry of their response functions—an archetypal example of unsupervised learning. The dominant framework for unsupervised learning in biology is Hebb’s principle, but how Hebbian learning could break such symmetries is a longstanding biophysical riddle. Theoretical studies argue that this requires inputs to the visual cortex to invert the relative magnitude of their correlations at long distances. Empirical measurements have searched in vain for such an inversion and report the opposite to be true. We formally approach the question through the Hermitianization of a multilayer model, which maps it into a problem of zero-temperature phase transitions. In the emerging phase diagram, both symmetries break spontaneously as long as (i) recurrent interactions are sufficiently long range and (ii) Hebbian competition is duly accounted for. A key ingredient for symmetry breaking is competition among connections sprouting from the same afferent cell. Such a competition, along with simple monotonic falloff of input correlations with distance, is capable of triggering the broken-symmetry phase required by image processing. We provide analytic predictions on the relative magnitudes of the relevant length scales needed for this novel mechanism to occur. These results reconcile experimental observations to the Hebbian paradigm, shed light on a new mechanism for visual cortex development, and contribute to our growing understanding of the relationship between learning and symmetry breaking.

Generating high-quality data (e.g., images or video) is one of the most exciting and challenging frontiers in unsupervised machine learning. Utilizing quantum computers in such tasks to potentially enhance conventional machine-learning algorithms has emerged as a promising application but poses big challenges due to the limited number of qubits and the level of gate noise in available devices. In this work, we provide the first practical and experimental implementation of a quantum-classical generative algorithm capable of generating high-resolution images of handwritten digits with state-of-the-art gate-based quantum computers. In our quantum-assisted machine-learning framework, we implement a quantum-circuit-based generative model to learn and sample the prior distribution of a generative adversarial network. We introduce a multibasis technique which leverages the unique possibility of measuring quantum states in different bases, hence enhancing the expressivity of the prior distribution. We train this hybrid algorithm on an ion-trap device based on ${}^{171}{\mathrm{Yb}}^{+}$ ion qubits to generate high-quality images and quantitatively outperform comparable classical generative adversarial networks trained on the popular MNIST dataset for handwritten digits.

Quantifying and comparing patterns of dynamical ecological systems requires averaging over measurable quantities. For example, to infer variation in movement and behavior, metrics such as step length and velocity are averaged over large ensembles. Yet, in nonergodic systems, such averaging is inconsistent; thus, identifying ergodicity breaking is essential in ecology. Using rich, high-resolution, movement data sets (greater than $7\times {10}^7$ localizations) from 70 individuals and continuous-time random walk modeling, we find subdiffusive behavior and ergodicity breaking in the localized movement of three species of avian predators. Small-scale, within-patch movement was found to be qualitatively different, not inferrable and separated from large-scale interpatch movement. Local search is characterized by long, power-law-distributed waiting times with a diverging mean, giving rise to ergodicity breaking in the form of considerable variability uniquely observed at this scale. This implies that wild animal movement is scale specific, with no typical waiting time at the local scale.

Semiconductor quantum dots in which electrons or holes are isolated via electrostatic potentials generated by surface gates are promising building blocks for semiconductor-based quantum technology. Here, we investigate double-quantum-dot (DQD) charge qubits in GaAs capacitively coupled to high-impedance superconducting quantum interference device array and Josephson-junction array resonators. We tune the strength of the electric-dipole interaction between the qubit and the resonator in situ using surface gates. We characterize the qubit-resonator coupling strength, the qubit decoherence, and the detuning noise affecting the charge qubit for different electrostatic DQD configurations. We find all quantities to be systematically tunable over more than one order of magnitude, resulting in reproducible decoherence rates ${\mathrm{\Gamma }}_2/2\pi <5\mathrm{MHz}$ in the limit of high interdot capacitance. In the opposite limit, by reducing the interdot capacitance, we increase the DQD electric-dipole strength and, therefore, its coupling to the resonator. Employing a Josephson-junction array resonator with an impedance of approximately $4\mathrm{k}\mathrm{\Omega }$ and a resonance frequency of ${\omega }_r/2\pi \sim 5.6\mathrm{GHz}$, we observe a coupling strength of $g/2\pi \sim 630\mathrm{MHz}$, demonstrating the possibility to operate electrons hosted in a semiconductor DQD in the ultrastrong-coupling regime (USC). The presented results are essential for further increasing the coherence of quantum-dot-based qubits and investigating USC physics in semiconducting QDs.

Quantum sensors such as spin defects in diamond have achieved excellent performance by combining high sensitivity with spatial resolution. Unfortunately, these sensors can only detect signal fields with frequency in a few accessible ranges, typically low frequencies up to the experimentally achievable control field amplitudes and a narrow window around the sensors’ resonance frequency. Here, we develop and demonstrate a technique for sensing arbitrary-frequency signals by using the sensor qubit as a quantum frequency mixer, enabling a variety of sensing applications. The technique leverages nonlinear effects in periodically driven (Floquet) quantum systems to achieve quantum frequency mixing of the signal and an applied bias ac field. The frequency-mixed field can be detected using well-developed sensing techniques such as Rabi and CPMG with the only additional requirement of the bias field. We further show that the frequency mixing can distinguish vectorial components of an oscillating signal field, thus enabling arbitrary-frequency vector magnetometry. We experimentally demonstrate this protocol with nitrogen-vacancy centers in diamond to sense a 150-MHz signal field, proving the versatility of the quantum mixer sensing technique.

Radiation properties of a pointlike source of light, such as a molecule or a semiconductor quantum dot, can be tailored by modifying its photonic environment. This phenomenon lies at the core of cavity quantum electrodynamics (CQED). Quantum dots in photonic crystal microcavities have served as a model system for exploring the CQED effects and for the realization of efficient single-photon quantum emitters. Recently, it has been suggested that quantum interference of the exciton recombination paths through the cavity and free-space modes can significantly modify the radiation. In this work, we report an unambiguous experimental observation of this fundamental effect in the emission spectra of site-controlled quantum dots positioned at prescribed locations within a photonic crystal cavity. The observed asymmetry in the polarization-resolved emission spectra strongly depends on the quantum dot position, which is confirmed by both analytical and numerical calculations. We perform quantum interferometry in the near-field zone of the radiation, retrieving the overlap and the position-dependent relative phase between the interfering free-space and cavity-mode-mediated radiative decays. The observed phenomenon is of importance for realization of photonic-crystal light emitters with near unity quantum efficiency. Our results suggest that the full description of light-matter interaction in the framework of CQED requires a modification of the conventional quantum master equation by also considering the radiation mode interference.

Optical qubits uniquely combine information transfer in optical fibers with a good processing capability and are therefore attractive tools for quantum technologies. A large challenge, however, is to overcome the low efficiency of two-qubit logic gates. The experimentally achieved efficiency in an optical controlled not (cnot) gate reached approximately 11% in 2003 and has seen no increase since. Here, we report on a new platform that was designed to surpass this long-standing record. The new scheme avoids inherently probabilistic protocols and, instead, combines aspects of two established quantum nonlinear systems: atom-cavity systems and Rydberg electromagnetically induced transparency. We demonstrate a cnot gate between two optical photons with an average efficiency of 41.7(5)% at a postselected process fidelity of 81(2)%. Moreover, we extend the scheme to a cnot gate with multiple target qubits and produce entangled states of presently up to five photons. All these achievements are promising and have the potential to advance optical quantum information processing in which almost all advanced protocols would profit from high-efficiency logic gates.

We demonstrate a new versatile building block for optical quantum technologies, enabling deterministic quantum engineering of light by combining the advantages of two complementary approaches: cavity quantum electrodynamics and interacting atomic ensembles. Our system is based on an intracavity Rydberg-blockaded atomic ensemble acting as a single two-level superatom. We coherently control its state and optically detect it in a single shot with 95% efficiency. Crucially, we demonstrate a superatom-state-dependent $\pi$ phase rotation on the light reflected from the cavity. Together with the state manipulation and detection, it is a key ingredient for implementing deterministic photonic entangling gates and for generating highly nonclassical light states.