Catalysts are substances that assist transformation of other resourceful objects without being consumed in the process. However, the fact that their “catalytic power” is limited and can be depleted is often overlooked, especially in the recently developing theories on catalysis of quantum randomness utilizing building correlation with catalyst. In this work, we establish a resource theory of one-shot catalytic randomness in which uncorrelatedness is consumed in catalysis of randomness. We do so by completely characterizing bipartite unitary operators that can be used to implement catalysis of randomness using partial transpose. By doing so, we find that every catalytic channel is factorizable, and therefore there exists a unital channel that is not catalytic. We define a family of catalytic entropies that quantifies catalytically extractable Rényi entropies from a quantum state and show how much the degeneracy of a quantum state can boost the catalytic entropy beyond its ordinary entropy. Based on this, we demonstrate that a randomness source can be actually exhausted after a certain amount of randomness is extracted. We apply this theory to systems under superselection rules that forbids superposition of certain quantum states and find that nonmaximally mixed states can yield the maximal catalytic entropy. We discuss implications of this theory to various topics, including catalytic randomness absorption, the no-secret theorem, and the possibility of multiparty infinite catalysis.

We show a pulse-efficient circuit transpilation framework for noisy quantum hardware. This is achieved by scaling cross-resonance pulses and exposing each pulse as a gate to remove redundant single-qubit operations with the transpiler. Crucially, no additional calibration is needed to yield better results than a CNOT-based transpilation. This pulse-efficient circuit transpilation therefore enables a better usage of the finite coherence time without requiring knowledge of pulse-level details from the user. As demonstration, we realize a continuous family of cross-resonance-based gates for SU(4) by leveraging Cartan's decomposition. We measure the benefits of a pulse-efficient circuit transpilation with process tomography and observe up to a 50% error reduction in the fidelity of $R_{ZZ}\left(\theta \right)$ and arbitrary SU(4) gates on IBM Quantum devices. We apply this framework for quantum applications by running circuits of the quantum approximate optimization algorithm applied to MAXCUT. For an 11-qubit nonhardware native graph, our methodology reduces the overall schedule duration by up to 52% and errors by up to 38%.

High-resolution imaging of ultracold atoms typically requires custom high numerical aperture (NA) optics, as is the case for quantum gas microscopy. These high NA objectives involve many optical elements, each of which contributes to loss and light scattering, making them unsuitable for quantum backaction limited “weak” measurements. We employ a low-cost high NA aspheric lens as an objective for a practical and economical—although aberrated—high-resolution microscope to image ${}^{87}\mathrm{Rb}$ Bose-Einstein condensates. Here, we present a methodology for digitally eliminating the resulting aberrations that is applicable to a wide range of imaging strategies and requires no additional hardware. We recover nearly the full NA of our objective, thereby demonstrating a simple and powerful digital aberration correction method for achieving optimal microscopy of quantum objects. This reconstruction relies on a high-quality measure of our imaging system's even-order aberrations from density-density correlations measured with differing degrees of defocus. We demonstrate our aberration compensation technique using phase-contrast imaging, a dispersive imaging technique directly applicable to quantum backaction limited measurements. Furthermore, we show that our digital correction technique reduces the contribution of photon shot noise to density-density correlation measurements which would otherwise contaminate the desired quantum projection noise signal in weak measurements.

In a recent work [S. Manna, P. Wei, Y. Xie, K. T. Law, P. A. Lee, and J. S. Moodera, Proc. Natl. Acad. Sci. 117, 8775 (2020)], signatures of a pair of Majorana bound states (MBSs) were found in an experimental platform formed by EuS islands deposited on top of a gold surface which was made superconducting through proximity coupling to a superconductor. In this paper, we provide a theoretical understanding for how MBSs can be formed in EuS/Au/superconductor heterostructures. We focus on the strip geometry where a narrow ferromagnetic strip is deposited on a planar structure. We first explicitly map out the topological phase diagram of the EuS/Au/superconductor heterostructure using the lattice Green's function method. Importantly, we find that the chemical potential step between the region with and without EuS covering is a crucial ingredient for the creation of MBS of this setup. Next, we focus on the Bogoliugov quasiparticles that are bound to the region under the EuS by Andreev reflections from the surrounding superconductors. Moreover, we obtain the topological regimes analytically using the scattering matrix method. Notably, we confirm that the normal reflections induced by the chemical potential step are essential for creating finite topological regimes. Furthermore, the area of the topological regimes shows periodic oscillation as a function of chemical potential as well as the sample width. We conclude by showing that the feromagnetic strip geometry holds a number of advantages over other quasi-one-dimensional schemes that have been proposed.

The brain works as a dynamic system to process information. Various challenges remain in understanding the connection between information and dynamics attributes in the brain. The present research pursues exploring how the characteristics of neural information functions are linked to neural dynamics. We attempt to bridge dynamics (e.g., Kolmogorov-Sinai entropy) and information (e.g., mutual information and Fisher information) metrics on the stimulus-triggered stochastic dynamics in neural populations. On the one hand, our unified analysis identifies various essential features of the information-processing-related neural dynamics. We discover spatiotemporal differences in the dynamic randomness and chaotic degrees of neural dynamics during neural information processing. On the other hand, our framework reveals the fundamental role of neural dynamics in shaping neural information processing. The neural dynamics creates an oppositely directed variation of encoding and decoding properties under specific conditions, and it determines the neural representation of stimulus distribution. Overall, our findings demonstrate a potential direction to explain the emergence of neural information processing from neural dynamics and help understand the intrinsic connections between the informational and the physical brain.

We construct a general gauging procedure of a pure matter theory on a lattice with a mixture of subsystem and global symmetries. This mixed symmetry can be either a semidirect product of a subsystem symmetry and a global symmetry, or a nontrivial extension of them. We demonstrate this gauging procedure on a cubic lattice in three dimensions with four examples: $G={\mathbb{Z}}_3^{\text{sub}}⋊{\mathbb{Z}}_2^{\text{glo}}, G=({\mathbb{Z}}_2^{\text{sub}}\times {\mathbb{Z}}_2^{\text{sub}})⋊{\mathbb{Z}}_2^{\text{glo}}, 1\to {\mathbb{Z}}_2^{\text{sub}}\to G\to {\mathbb{Z}}_2^{\text{glo}}\to 1$, and $1\to {\mathbb{Z}}_2^{\text{sub}}\to G\to K_4^{\text{glo}}\to 1$. The former two cases and the last one produce the non-Abelian fracton orders. Our construction provides an identification of the electric charges of these fracton orders with irreducible representations of the symmetry. Furthermore, by constraining the local Hilbert space, the magnetic fluxes with different geometry (tube-like and plaquette-like) satisfy a subalgebra of the quantum double models (QDMs). This algebraic structure leads to an identification of the magnetic fluxes to the conjugacy classes of the symmetry.

The Leggett-Garg inequality (LGI) distinguishes nonmacrorealistic channels from macrorealistic ones by constraining the experimental outcomes of the underlying system. In this work, we propose a class of channels which, initially, cannot violate the LGI (in the form of the temporal Bell inequality) but can violate it after the application of stochastic pre- and post-operations (SPPOs). As a proof-of-principle experiment, we demonstrate the stochastic pre- and post-operations in an amplitude-damping channel with photonic qubits. We denote the above phenomenon as hidden nonmacrorealistic channels. We also discuss the relationship between these hidden nonmacrorealistic channels [in terms of the temporal Clauser-Horne-Shimony-Holt (CHSH) inequality] and the strongly nonlocality-breaking channel, which breaks the hidden spatial CHSH nonlocality for arbitrary states. In general, if the channel satisfies hidden nonmacrorealism, it is not a strongly CHSH nonlocality-breaking channel.

The existence of a gapped chiral spin liquid has been recently suggested in the vicinity of the metal-insulator transition of the Hubbard model on the triangular lattice, by intensive density-matrix renormalization group (DMRG) simulations [A. Szasz, J. Motruk, M. P. Zaletel, and J. E. Moore, Phys. Rev. X 10, 021042 (2020)]. Here, we report the results obtained within the variational Monte Carlo technique based upon Jastrow-Slater wave functions, implemented with backflow correlations. As in DMRG calculations, we consider $N$-leg cylinders. For $N=4$ and in the presence of a next-nearest-neighbor hopping, a chiral spin liquid emerges between the metal and the insulator with magnetic quasi-long-range order. Within our approach, the chiral state is gapped and breaks the reflection symmetry. By contrast, for both $N=5$ and 6, the chiral spin liquid is not the state with the lowest variational energy: in the former case, a nematic spin liquid is found in the entire insulating regime, while for the less frustrated case with $N=6$ the results are very similar to that obtained on two-dimensional clusters [L. F. Tocchio, A. Montorsi, and F. Becca, Phys. Rev. B 102, 115150 (2020)], with an antiferromagnetic phase close to the metal-insulator transition and a nematic spin liquid in the strong-coupling regime.

Phase separation is not only ubiquitous in diverse physical systems, but also plays an important organizational role inside biological cells. However, experimental studies of intracellular condensates (drops with condensed concentrations of specific collections of proteins and nucleic acids) have challenged the standard coarsening theories of phase separation. Specifically, the coarsening rates observed are unexpectedly slow for many intracellular condensates. Recently, Folkmann et al. [Science 373, 1218 (2021)] argued that the slow coarsening rate can be caused by the slow conversion of a condensate constituent between the state in the dilute phase and the condensate state. One implication of this conversion-limited picture is that standard theories of coarsening in phase separation (Lifshitz-Slyozov-Wagner theory of Ostwald ripening and drop coalescence schemes) no longer apply. Surprisingly, I show here that the model equations of conversion-limited phase separation can instead be mapped onto a grain growth model in a single-phase material in three dimensions. I further elucidate the universal coarsening behavior in the late stage using analytical and numerical methods.

Considering time-harmonic optical fields, we put forward the complex helicity and its alternating flow, together with their conservation equation: the complex helicity theorem. Its imaginary part constitutes a novel law that rules the build-up of what we establish as the reactive helicity through its zero time-average flow. Its associated reactive flow and the imaginary Poynting momentum that accounts for the accretion of reactive power are illustrated in two paradigmatic systems: evanescent waves and fields scattered from magnetodielectric dipolar nanoparticles. As for the former, we show that its reactive helicity may be experimentally observed as we introduce a reactive spin momentum and a reactive orbital momentum in terms of which we express the imaginary field momentum, whose transversal component produces an optical force on a magnetoelectric particle that, as we illustrate, may surpass and can be discriminated from the known force due to the so-called extraordinary momentum. We also uncover a nonconservative force on such a magnetoelectric particle, acting in the decay direction of the evanescent wave, and that may also be discriminated from the standard gradient force; thus making the reactive power of the wavefield also observable. Concerning the light scattered by magnetoelectric nanoparticles, we establish two optical theorems that govern the accretion of reactive helicity and reactive power on extinction of incident wave helicity and energy. Like a nule total, i.e., internal plus external, reactive power is at the root of a resonant scattered power, we show that a zero total reactive helicity underlies a resonant scattered helicity. These reactive quantities are shown to yield a novel interpretation of the two Kerker conditions, which we demonstrate to be linked to an absence, or minimum, of the overall scattered reactive energy. Further, we demonstrate that the first Kerker condition, under which the particle becomes dual on illumination with circularly polarized light, amounts to a nule overall scattered reactive helicity. Therefore these two reactive quantities are shown to underly the directivity of the particle scattering and emission. In addition, we discover a discriminatory property of the reactive helicity of chiral light incident on a chiral nanoparticle by excitation of the external reactive power. This should be useful for optical near field enantiomeric separation, an effect that we call reactive dichroism.

We present the digital signal processing of a mutually entangled, two-mode squeezed state using Wiener filtering to maximize the reduction of quantum noise of a single mode. By conditioning this mode, the signal, with its directly detected entangled pair, the witness, we show quantum noise cancellation of 2 dB below that of the signal vacuum level. We present the frequency-dependent digital recovery of squeezed states with Wiener filtering. This filtering is particularly relevant for gravitational wave detectors which will seek to use frequency-dependent squeezed states to improve their reach to the observable universe. We demonstrate the recovery of squeezed states in a configuration that replicates one which would provide optimum sensitivity improvement in a gravitational wave detector under the effects of radiation pressure noise. More generally, this technique may find application in other quantum-limited high-precision experiments such as those using optomechanical cavities.

Spectroscopy is a powerful tool to probe physical, chemical, and biological systems. Recent advances in microfabrication have introduced novel, intriguing mesoscopic quantum systems including superconductor-semiconductor hybrid devices and topologically nontrivial electric circuits. A sensitive, general-purpose spectrometer to probe the energy levels of these systems is lacking. We propose an on-chip absorption spectrometer functioning well into the millimeter wave band which is based on a voltage-biased superconducting quantum interference device. We demonstrate the capabilities of the spectrometer by coupling it to a variety of superconducting systems, probing phenomena such as quasiparticle and plasma excitations. We perform spectroscopy of a microscopic tunable nonlinear resonator in the 40–50-GHz range and measure transitions to highly excited states. The Josephson junction spectrometer, with outstanding frequency range, sensitivity, and coupling strength will enable new experiments in linear and nonlinear spectroscopy of novel mesoscopic systems.

A complex interplay of single-neuron properties and the recurrent network structure shapes the activity of cortical neurons. The single-neuron activity statistics differ in general from the respective population statistics, including spectra and, correspondingly, autocorrelation times. We develop a theory for self-consistent second-order single-neuron statistics in block-structured sparse random networks of spiking neurons. In particular, the theory predicts the neuron-level autocorrelation times, also known as intrinsic timescales, of the neuronal activity. The theory is based on an extension of dynamic mean-field theory from rate networks to spiking networks, which is validated via simulations. It accounts for both static variability, e.g., due to a distributed number of incoming synapses per neuron, and temporal fluctuations of the input. We apply the theory to balanced random networks of generalized linear model neurons, balanced random networks of leaky integrate-and-fire neurons, and a biologically constrained network of leaky integrate-and-fire neurons. For the generalized linear model network with an error function nonlinearity, a novel analytical solution of the colored noise problem allows us to obtain self-consistent firing rate distributions, single-neuron power spectra, and intrinsic timescales. For the leaky integrate-and-fire networks, we derive an approximate analytical solution of the colored noise problem, based on the Stratonovich approximation of the Wiener-Rice series and a novel analytical solution for the free upcrossing statistics. Again closing the system self-consistently, in the fluctuation-driven regime, this approximation yields reliable estimates of the mean firing rate and its variance across neurons, the interspike-interval distribution, the single-neuron power spectra, and intrinsic timescales. With the help of our theory, we find parameter regimes where the intrinsic timescale significantly exceeds the membrane time constant, which indicates the influence of the recurrent dynamics. Although the resulting intrinsic timescales are on the same order for generalized linear model neurons and leaky integrate-and-fire neurons, the two systems differ fundamentally: for the former, the longer intrinsic timescale arises from an increased firing probability after a spike; for the latter, it is a consequence of a prolonged effective refractory period with a decreased firing probability. Furthermore, the intrinsic timescale attains a maximum at a critical synaptic strength for generalized linear model networks, in contrast to the minimum found for leaky integrate-and-fire networks.

We theoretically derive and experimentally compare several different ways to access entropy production in a quantum process under feedback control. We focus on a bipartite quantum system realizing an autonomous Maxwell's demon scheme reported by Najera-Santos et al. [Phys. Rev. Research 2, 032025(R) (2020)], where information encoded in a demon is consumed to transfer heat from a cold qubit to a hot cavity. By measuring individual quantum trajectories of the joint demon-cavity-qubit system, we compute the entropy production with six distinct expressions derived from different approaches to the system description and its evolution. Each method uses a specific set of trajectories and data processing. Our results provide a unified view of the various meanings of irreversibility in quantum systems and pave the way for the measurement of entropy production beyond thermal frameworks.

The implementation of a combination of continuous weak measurement and classical feedback provides a powerful tool for controlling the evolution of quantum systems. In this paper, we investigate the potential of this approach from three perspectives. First, we consider a double-well system in the classical large-atom-number limit, deriving the exact equations of motion in the presence of feedback. Second, we consider the same system in the limit of small atom number, revealing the effect that quantum fluctuations have on the feedback scheme. Finally, we explore the behavior of modest-sized Hubbard chains using exact numerics, demonstrating the near-deterministic preparation of number states, a tradeoff between local and nonlocal feedback for state preparation, and evidence of a feedback-driven symmetry-breaking phase transition.

Emergent dynamics of complex systems are observed throughout nature and society. The coordinated motion of bird flocks, the spread of opinions, fashions and fads, or the dynamics of an epidemic, are all examples of complex macroscale phenomena that arise from fine-scale interactions at the individual level. In many scenarios, observations of the system can only be made at the macroscale, while we are interested in creating and fitting models of the microscale dynamics. This creates a challenge for inference as a formal mathematical link between the microscale and macroscale is rarely available. Here, we develop an inferential framework that bypasses the need for a formal link between scales and instead uses sparse Gaussian process regression to learn the drift and diffusion terms of an empirical Fokker-Planck equation, which describes the time evolution of the probability density of a macroscale variable. This gives us access to the likelihood of the microscale properties of the physical system and a second Gaussian process is then used to emulate the log-likelihood surface, allowing us to define a fast, adaptive MCMC sampler, which iteratively refines the emulator when needed. We illustrate the performance of our method by applying it to a simple model of collective motion.

A fundamental objective in quantum information science is to determine the cost in classical resources of simulating a particular quantum system. The classical simulation cost is quantified by the signaling dimension which specifies the minimum amount of classical communication needed to perfectly simulate a channel's input-output correlations when unlimited shared randomness is held between encoder and decoder. This paper provides a collection of device-independent tests that place lower and upper bounds on the signaling dimension of a channel. Among them, a single family of tests is shown to determine when a noisy classical channel can be simulated using an amount of communication strictly less than either its input or its output alphabet size. In addition, a family of eight signaling dimension witnesses is presented that completely characterize when any four-outcome measurement channel, such as a Bell measurement, can be simulated using one communication bit and shared randomness. Finally, we bound the signaling dimension for all partial replacer channels in $d$ dimensions. The bounds are found to be tight for the special case of the erasure channel.