We investigate the quasiparticle dynamics in ${\mathrm{MnBi}}_2{\mathrm{Te}}_4$ single crystals using ultrafast optical spectroscopy. Our results show that there exist anomalous dynamical optical responses below the antiferromagnetic (AFM) ordering temperature $T_N$. In specific, we reveal that both the initial carrier decay and recombination processes can be modulated via introducing the AFM order in subpicosecond and picosecond timescales, respectively. We also discover a long relaxation process emerging below $T_N$ with a timescale approaching the nanosecond regime, and can be attributed to the $T$-dependent spin-lattice interaction. There also emerges an unusual phonon energy renormalization below $T_N$, which is found to arise from its coupling to the spin degree via the exchange interaction and magnetic anisotropy. Our findings provide key information for understanding the dynamical properties of nonequilibrium carrier, spin, and lattice in ${\mathrm{MnBi}}_2{\mathrm{Te}}_4$.

We introduce a model-independent method for the efficient simulation of low-entropy systems, whose dynamics can be accurately described with a limited number of states. Our method leverages the time-dependent variational principle to efficiently integrate the Lindblad master equation, dynamically identifying and modifying the low-rank basis over which we decompose the system's evolution. By dynamically adapting the dimension of this basis, and thus the rank of the density matrix, our method maintains optimal representation of the system state, offering a substantial computational advantage over existing adaptive low-rank schemes in terms of both computational time and memory requirements. We demonstrate the efficacy of our method through extensive benchmarks on a variety of model systems, with a particular emphasis on multiqubit bosonic codes, a promising candidate for fault-tolerant quantum hardware. Our results highlight the method's versatility and efficiency, making it applicable to a wide range of systems characterized by arbitrary degrees of entanglement and moderate entropy throughout their dynamics. We provide an implementation of the method as a Julia package, making it readily available to use.

In the macroscopic world, time is intrinsically asymmetric, flowing in a specific direction, from past to future. However, the same is not necessarily true for quantum systems, as some quantum processes produce valid quantum evolutions under time reversal. Supposing that such processes can be probed in both time directions, we can also consider quantum processes probed in a coherent superposition of forward and backward time directions. This yields a broader class of quantum processes than the ones considered so far in the literature, including those with indefinite causal order. In this work, we demonstrate an operation belonging to this class: the quantum time flip. Using a photonic realisation of this operation, we apply it to a game formulated as a discrimination task between two sets of operators. This game not only serves as a witness of an indefinite time direction, but also allows for a computational advantage over strategies using a fixed time direction, and even those with an indefinite causal order.

The ecological and evolutionary dynamics of large populations can be addressed theoretically using concepts and methodologies from statistical mechanics. This approach has been extensively discussed in the literature, both within the realm of population genetics, which focuses on genes or “genotypes,” and in adaptive dynamics, which emphasizes traits or “phenotypes.” Following this tradition, here we construct a theoretical framework allowing us to derive “macroscopic” evolutionary equations from a general “microscopic” stochastic dynamics representing the fundamental processes of reproduction, mutation, and selection in a large community of individuals, each one characterized by its phenotypic features. Importantly, in our setup, ecological and evolutionary timescales are intertwined, which makes it particularly suitable to describe microbial communities, a timely topic of utmost relevance. The framework leads to a probabilistic description—even in the case of arbitrarily large populations—of the distribution of individuals in phenotypic space as encoded in what we call the “generalized Crow-Kimura equation” or “generalized replicator-mutator equation.” We discuss the limits in which such an equation reduces to the (deterministic) theory of “adaptive dynamics,” i.e., the standard approach to evolutionary dynamics in phenotypic space. Moreover, we emphasize the aspects of the theory that are beyond the reach of standard adaptive dynamics. In particular, by developing a simple model of a growing and competing population as an illustrative example, we demonstrate that the resulting probability distribution can undergo “dynamical phase transitions.” These transitions may involve shifts from a unimodal distribution to a bimodal distribution, generated by an evolutionary branching event, or to a multimodal distribution through a cascade of evolutionary branching events. Furthermore, our formalism allows us to rationalize these cascades using the parsimonious approach of Landau's theory of phase transitions. Finally, we extend the theory to account for finite populations and illustrate the possible consequences of the resulting stochastic or “demographic” effects. Altogether, the present framework extends and/or complements existing approaches to evolutionary and adaptive dynamics and paves the way to more systematic studies of microbial communities as well as to future developments including theoretical analyses of the evolutionary process from the general perspective of nonequilibrium statistical mechanics.

In this paper, we introduce a generic strategy to accelerate and improve the overall performance of machine-learning algorithms, both in their classical and quantum versions, heavily rely on optimization algorithms based on gradients, such as gradient descent. The overall performance is dependent on the appearance of local minima and barren plateaus, which slow down calculations and lead to nonoptimal solutions. In practice, this results in dramatic computational and energy costs for artificial intelligence applications. Our method is based on coordinate transformations, like variational rotations, adding extra directions in parameter space that depend on the cost function itself, and which allowus to explore the configuration landscape more efficiently. The validity of our method is benchmarked by boosting several quantum machine-learning algorithms, getting a very significant improvement in their performance.

We study Floquet systems with translationally invariant nearest-neighbor two-site gates. Depending on the order in which the gates are applied on an $N$-site system with periodic boundary conditions, there are factorially many different circuit configurations. We prove that there are only $N-1$ different spectrally equivalent classes, which can be viewed either as a generalization of the brick wall or of the staircase configuration. Every class, characterized by two integers, has a nontrivial space-time symmetry with important implications for the level-spacing distribution—a standard indicator of quantum chaos. Namely, in order to study chaoticity one should not look at eigenphases of the Floquet propagator itself, but rather at the spectrum of an appropriate root of the propagator.

Skyrmion qubits are a new highly promising logic element for quantum information processing. However, their scalability to multiple interacting qubits remains challenging. We propose a hybrid quantum setup with skyrmion qubits strongly coupled to nanomechanical cantilevers via magnetic coupling, which harnesses phonons as quantum interfaces for the manipulation of distant skyrmion qubits. A linear drive is utilized to achieve the modulation of the stiffness coefficient of the cantilever, resulting in an exponential enhancement of the coupling strength between the skyrmion qubit and the mechanical mode. We also consider the case of a topological resonator array, which allows us to study interactions between skyrmion qubits and topological phonon band structure, as well as chiral skyrmion-skyrmion interactions. The scheme suggested here offers a fascinating platform for investigating quantum information processing and quantum simulation with magnetic microstructures.

Understanding intermittency, a ubiquitous behavior in flows of packed grains, is pivotal for establishing the rheology of granular matter. A straightforward explanation has been missing despite the long development of theories at various levels of abstraction. Here, we propose the use of a Stribeck-Hertz model that starts with the classic Coulomb friction but takes into account the interparticle tribology, i.e., the reduction of friction coefficient with sliding speed as is commonly observed. Our numerical experiments reveal a state diagram that covers a wide range of packing fractions and show that incorporating the tribology enables the occurrence of quaking intermittency in the midrange of a dimensionless shear rate, consistent with prior experimental observations. Further study of the discontinuities in the evolution of the mean contact number leads to our discovery of two types of quaking that are distinguished by the abrupt increase or decrease of neighboring contacts and reveal different pathways of microstructural change underlying these discrete events. In contrast to the prevailing paradigm in which shear is believed to promote jamming at intermediate densities, our study demonstrates that shear can also unjam a granular system, and this occurrence depends on the shear rate.

Fast, high-fidelity control and readout of protected superconducting qubits are fundamentally challenging due to their inherent insensitivity. We propose a flux qubit variation which enjoys a tunable level of protection against relaxation to resolve this outstanding issue. Our qubit design, the double-shunted flux qubit (DSFQ), realizes a generic double-well potential through its three-junction ring geometry. One of the junctions is tunable, making it possible to control the barrier height and thus the level of protection. We analyze single- and two-qubit gate operations that rely on lowering the barrier. We show that this is a viable method that results in high-fidelity gates as the noncomputational states are not occupied during operations. Further, we show how the effective coupling to a readout resonator can be controlled by adjusting the externally applied flux while the DSFQ is protected from decaying into the readout resonator. Finally, we also study a double-loop gradiometric version of the DSFQ which is exponentially insensitive to variations in the global magnetic field, even when the loop areas are nonidentical.

We propose and analyze the use of Bayesian optimization techniques to design quantum annealing schedules with minimal user and resource requirements. We showcase our scheme with results for two paradigmatic spin models. We find that Bayesian optimization is able to identify schedules resulting in fidelities several orders of magnitude better than standard protocols for both quantum and reverse annealing, as applied to the $p$-spin model. We also show that our scheme can help improve the design of hybrid quantum algorithms for hard combinatorial optimization problems, such as the maximum independent set problem, and illustrate these results via experiments on a neutral-atom quantum processor available on Amazon Braket.

Brillouin scattering in microresonators has emerged as the driving process for developing high-coherence lasers for applications such as coherent optical communications, optical atomic clocks, microcomb solitons, and quantum communications. However, most of the demonstrations of microresonator Brillouin lasers have been limited to a 1550 nm wavelength regime, which benefits from the development of low-loss microresonator devices on different material platforms and the availability of tunable pump lasers. The development of wide bandwidth thulium-doped fiber amplifiers and low two-photon absorption in silicon around $2\mu \mathrm{m}$ makes this wavelength region a potential candidate for applications in future optical communications, gravitation wave sensing, and atmospheric sensing. All these applications will benefit from the development of Brillouin lasers. However, there has not been much progress on microresonator-based $2\mu \mathrm{m}$ Brillouin lasers. Here, we present a demonstration of a $2\mu \mathrm{m}$ microresonator Brillouin laser. We use whispering gallery mode resonances in a $\sim 330\mu \mathrm{m}$ silica microsphere to demonstrate a Brillouin lasing threshold of 35 mW. We achieve generation of second- and third-order Brillouin Stokes using pump powers of $\sim 60\mathrm{mW}$ and 104 mW, respectively. By tuning the pump laser wavelength, we demonstrate high-resolution ($\sim 10$ pm) tuning of the Brillouin laser. From the beat signal of the first- and third-order Brillouin Stokes, we estimate a Brillouin laser linewidth of $\sim 135\mathrm{kHz}$, which is 15 times smaller than the pump linewidth. This work may find applications in optical communications, soliton combs, and atmospheric sensing in the $2\mu \mathrm{m}$ wavelength region.

The efficiency of a Bell-state measurement on photon pairs is bound to 50% due to the number of Bell states that can be distinguished using linear optics. Here we present the implementation of a protocol that allows us to distinguish all four Bell states by the use of a single-ion quantum memory and heralded absorption as state-selective measurement. The protocol is implemented in two steps. First we demonstrate the state-preserving mapping of a photonic qubit onto the quantum memory, verified by the preservation of entanglement in the process. Then we demonstrate the full Bell-state projection between a memory qubit and an incoming photonic qubit, by applying it for atom-to-photon quantum-state teleportation.

We theoretically investigate non-Hermitian $p$-wave Fermi superfluidity in one-dimensional spin-polarized Fermi gases which is relevant to recent ultracold atomic experiments. Considering an imaginary atom-dimer coupling responsible for the three-body recombination process in the Lindblad formalism, we discuss the stability of the superfluid state against the atomic loss effect. Within the two-channel non-Hermitian BCS-Eagles-Leggett theory, the atomic loss is characterized by the product of the imaginary atom-dimer coupling and the $p$-wave effective range. Our results indicate that for a given imaginary atom-dimer coupling, a smaller magnitude of the effective ranges of $p$-wave interaction is crucial for reaching the non-Hermitian $p$-wave Fermi superfluid state. Moreover, our theoretical framework for many-body systems with the three-body loss, which is inevitable in ultracold atoms, would promote further progress in non-Hermitian cold-atomic physics.

Anomalous Floquet topological superconductivity with chirality can be achieved by applying a dc-bias voltage across the Josephson junction with a sandwiched magnetic topological insulator (TI), in which the intrinsic Josephson phase provides a time-dependent periodic driving [R.-X. Zhang and S. Das Sarma, Phys. Rev. Lett. 127, 067001 (2021)]. In this work, we remove the bias voltage and connect the magnetic TI to an external AC voltage source to modulate the chemical potential, thus bringing about an explicit-time Floquet periodic driving. In the context of the driving, the system is similarly found to convert into a two-dimensional anomalous Floquet topological superconductor with chirality. By tuning the AC voltage source's frequency, we obtain a rich variety of novel Floquet topological superconducting phases with chirality. Particularly, by manipulating such static parameters as Zeeman field and superconducting pairing potential, a series of topological superconducting phase transitions are also exhibited, accompanied by exotic Floquet topological superconducting phases with chirality.

The electromagnetic Casimir effect has a fermionic counterpart in topological insulators: Zero-point fluctuations of a massless Dirac fermion field mediate a force between magnetic scatterers. The Casimir force is insensitive to disorder that preserves the topological protection of an unpaired Dirac cone. The protection may be broken if the Dirac equation is discretized, and an exponential suppression of the Casimir effect will result if a gap opens at the Dirac point. Here, we show how this lattice artifact may be avoided, by applying a recently developed local discretization of the Euclidean action that does not suffer from the fermion-doubling obstruction of local discretizations of the Hamiltonian.

Transformers are neural networks that revolutionized natural language processing and machine learning. They process sequences of inputs, like words, using a mechanism called self-attention, which is trained via masked language modeling (MLM). In MLM, a word is randomly masked in an input sequence, and the network is trained to predict the missing word. Despite the practical success of transformers, it remains unclear what type of data distribution self-attention can learn efficiently. Here, we show analytically that if one decouples the treatment of word positions and embeddings, a single layer of self-attention learns the conditionals of a generalized Potts model with interactions between sites and Potts colors. Moreover, we show that training this neural network is exactly equivalent to solving the inverse Potts problem by the so-called pseudolikelihood method, well known in statistical physics. Using this mapping, we compute the generalization error of self-attention in a model scenario analytically using the replica method.