Learning mixed quantum states in large-scale experiments

This article presents an efficient and parallelized implementation of the density matrix renormalization group (DMRG) algorithm for quantum chemistry calculations. The DMRG method as a large-scale multireference electronic structure model is by nature particularly efficient for one-dimensionally correlated systems, while the present development is oriented toward applications for polynuclear transition metal compounds, in which the macroscopic one-dimensional structure of electron correlation is absent. A straightforward extension of the DMRG algorithm is proposed with further improvements and aggressive optimizations to allow its application with large multireference active space, which is often demanded for metal compound calculations. Special efficiency is achieved by making better use of sparsity and symmetry in the operator and wave function representations. By accomplishing computationally intensive DMRG calculations, the authors have found that a large number of renormalized basis states are required to represent high entanglement of the electron correlation for metal compound applications, and it is crucial to adopt auxiliary perturbative correction to the projected density matrix during the DMRG sweep optimization in order to attain proper convergence to the solution. Potential energy curve calculations for the Cr(2) molecule near the known equilibrium precisely predicted the full configuration interaction energies with a correlation space of 24 electrons in 30 orbitals [denoted by (24e,30o)]. The energies are demonstrated to be accurate to 0.6mE(h) (the error from the extrapolated best value) when as many as 10,000 renormalized basis states are employed for the left and right DMRG block representations. The relative energy curves for [Cu(2)O(2)](2+) along the isomerization coordinate were obtained from DMRG and other correlated calculations, for which a fairly large orbital space (32e,62o) is modeled as a full correlation space. The DMRG prediction nearly overlaps with the energy curve from the coupled cluster with singles, doubles, and perturbative triple [CCSD(T)] calculations, while the multireference complete active space self-consistent field (CASSCF) calculations with the small reference configuration (8e,8o) are found to overestimate the biradical character of the electronic state of [Cu(2)O(2)](2+) according to the one-electron density matrix analysis.

The observation of genuine quantum effects in systems governed by non-Hermitian Hamiltonians has been an outstanding challenge in the field. Here we simulate the evolution under such Hamiltonians in the quantum regime on a superconducting quantum processor by using a dilation procedure involving an ancillary qubit. We observe the parity–time ({mathcal{PT}})-symmetry breaking phase transition at the exceptional points, obtain the critical exponent, and show that this transition is associated with a loss of state distinguishability. In a two-qubit setting, we show that the entanglement can be modified by local operations.

Periodically driven systems, or Floquet systems, exhibit many novel dynamics and interesting out-of-equilibrium phases of matter. Those phases arising with the quantum systems' symmetries, such as global U(1) symmetry, can even show dynamical stability with symmetry protection. Here we experimentally demonstrate a U(1) symmetry-protected prethermal phase, via performing a digital-analog quantum simulation on a superconducting quantum processor. The dynamical stability of this phase is revealed by its robustness against external perturbations. We also find that the site-averaged square of the two-spin correlation function in this phase is stabilized by the interaction between the spins. Our work reveals a promising prospect in discovering emergent quantum dynamical phases with digital-analog quantum simulators.

The understanding of quantum mechanical systems is essential to modern physics and its applications. However, already for entangled systems of a few tens of constituents, exact numerical simulations on classical computers can become impossible. Quantum simulators based on well-controlled quantum system might provide the only effective approach to these systems. Trapped atomic ions offer a uniquely precise and controllable platform. They are used as platforms for, e.g., future quantum computers, quantum simulators, and extremely precise clocks. Quantum-simulation problems of interest and out-of-reach for modern theoretical methods include the dynamics of one-dimensional systems on long time scales and more-than-one dimensional systems with long-range interaction. For the latter, two-dimensional arrays of ions, individually trapped and controlled above microfabricated surface-electrode traps, present a promising approach. In the first realizations so far, the inter-site distance between the ions was too large to allow for sufficient inter-site coupling. We aim for a scalable approach to an analog quantum simulator based on a two-dimensional array of individually trapped ions. As a first demonstration, we operate an array of three magnesium ions in triangular arrangement with a side-length of 40µm. Therein, we previously demonstrated the individual control of internal (electronic) and external (motional) degrees of freedom of the ions. Here, we present the first realization of inter-site coupling in the two-dimensional array. We demonstrate the coupling by a transfer of large coherent states of motion between the sites. We investigate the influence of the amplitude of these motional states in the anharmonic trapping potential and extrapolate to future experiments on the single-phonon level. We apply the real-time control of the coupling and concatenate the two-site coupling to transfer motional excitation between all three sites of the array. To demonstrate the scalability of our techniques, we couple all three sites simultaneously and investigate the evolution of an initial excitation at one and two sites of the array. The latter shows interference effects of the different pathways in the triangle. Current motional heating rates on the order of the inter-site coupling, preclude working with single phonons near the motional ground-state. We present a new experimental apparatus and vacuum chamber which will allow in-situ cleaning of surface-electrode traps. This has shown to reduce motional heating rates by two orders of magnitude. In this apparatus, we additionally realize a magnetic-field insensitive qubit in 25Mg+ with a coherence time exceeding six seconds. We generate the magnetic field around 10.9mT by a hybrid magnet assembly based on solid-state magnets and fine-tuned by electric coils. Once we have reduced the heating rate in the triangle trap array using the new setup, first quantum simulation experiments, investigating spin-frustration or artificial gauge fields, will come in reach. Here our triangle represents a basic, scalable, building block of future latices designed at will.

Interaction between pyroclastic density currents and buildings: Numerical simulation and first experiments

The Google Quantum AI team's long-term goal is to realize a large-scale fault-tolerant quantum computer. Of the technologies available to implement the quantum processor at the core of such a system, solid-state superconducting circuits based on Josephson junctions (JJs) are among the strongest contenders. Recent demonstrations with this technology include computation beyond the capabilities of today's most powerful supercomputers [1] and execution of quantum error correction (QEC) codes that can detect and correct either bit or phase flip errors [2]. These exciting results were enabled by low-error-rate quantum processors with tens of qubits and the supporting infrastructure to run these devices. However, today's quantum computers still have orders of magnitude fewer qubits than is required for a useful fault-tolerant quantum computer; for this, an estimated million or more qubits will be needed and scaling-up today's technology to this extent is non-trivial. Here, we review the Google Quantum AI team's recent progress and future plans. Specifically, we describe our post-classical Sycamore quantum computer and discuss the Google Quantum AI roadmap to fault-tolerant quantum computing.

We investigate the role of the permutationally invariant part of the density matrix (PIDM) in capturing the properties of the ground state of the system during a quantum phase transition. In the context of quantum state tomography, PIDM is known to be obtainable with only a low number of measurement settings, namely $O({L}^{2})$, where $L$ is the system size. Considering the transverse-field Ising chain and the $XXZ$ chain as examples, we compute the second-order R\'enyi entropy of PIDM for the ground state by using the density-matrix renormalization-group algorithm. In the transverse-field Ising chain with ferromagnetic interaction, the ground state is permutationally invariant both in the limits of zero and infinite field, leading to a vanishing R\'enyi entropy of PIDM. The latter exhibits a broad peak as a function of the transverse field around the quantum critical point, which gets more pronounced for larger system size. In the antiferromagnetic case, the peak structure disappears and the R\'enyi entropy diverges like $O(L)$ in the whole field range of the ordered phase. In the $XXZ$ model with ferromagnetic interaction, the ground state is permutationally invariant in the full parameter regime of easy-axis anisotropy, causing the R\'enyi entropy of PIDM to vanish. In the easy-plane region, the R\'enyi entropy of PIDM grows almost linearly as a function of the system size. In the antiferromagnetic case, the R\'enyi entropy of PIDM takes finite values at any point in parameter space; importantly, its minimum appears at the phase-transition point. We discuss the cause of these behaviors of the R\'enyi entropy of PIDM, examining the possible application of this experimentally tractable quantity to the analysis of phase-transition phenomena.

While the universal quantum computer seems not in reach for the near future, this work focusses on analog quantum simulation of intriguing quantum models of light-matter interactions, with the goal of achieving a computational speed-up as compared to classical hardware. Existing building blocks of quantum hardware are used from superconducting circuits, that have proven to be a very suitable experimental platform for the implementation of model Hamiltonians at a high degree of controllability.

Alternatively to the full reconstruction of an unknown quantum process, the so-called selective and efficient quantum process tomography (SEQPT) allows estimating, individually and up to the required accuracy, a given element of the matrix that describes such an operation with a polynomial amount of resources. The implementation of this protocol has been carried out with success to characterize the evolution of a quantum system that is well described by a trace-preserving quantum map. Here, we deal with a more general type of quantum process that does not preserve the trace of the input quantum state, which naturally arises in the presence of imperfect devices and system-environment interactions, in the context of quantum information science or quantum dynamics control. In that case, we show with the aid of a priori information on the losses structure of the quantum channel that the SEQPT reconstruction can be adapted to reconstruct the non-trace-preserving map. We explicitly describe how to implement the reconstruction in an arbitrary Hilbert space of finite dimension $d$. The method is experimentally verified on a superconducting quantum processor provided by IBM Quantum services, by estimating several non-trace-preserving quantum processes in dimensions up to $d=6$. Our results show that it is possible to efficiently reconstruct non-trace-preserving processes, with high precision, and with significantly higher fidelity than when the process is assumed to be trace preserving.

Replication of large—scale experiments is desirable, but the numbers of replicates needed are not known. Costs and feasibility of ecosystem experiments depend critically on the numbers of replicates needed because of the high cost per replicate and the scarcity of experimental ecosystems. This paper examines the numbers of replicates and magnitudes of manipulation needed to detect changes in lake primary productivity resulting from piscivore manipulations. Substantial (°10 x changes in the independent variable, piscivore biomass) and sustained (at least 3—5 yr) manipulations using five reference and five experimental ecosystems produced significant t test results in >80% of simulated experiments. The need for substantial and sustained manipulations is consistent with published results of whole—lake experiments on nutrient inputs, chemical contaminants, and the biota. In many cases, limited numbers of experimental systems or high costs will prevent adequate replication of ecosystem experiment. When large—scale experiments employ insufficient (e.g., 2 or 3) replicates and/or modest perturbations of the independent variate, there is great risk of erroneously accepting the hypothesis of no treatment effect. Therefore, unreplicated paired—system experiments (one reference and one experimental system) are often preferable even though classical statistics cannot be used to determine whether manipulation caused a change in the experimental system. A series of unreplicated paired—system experiments, staggered in time and performed in many locations, will provide more ecological insight than a replicated experiment in a single region. Few statistical methods pertain to large—scale ecological experiments; innovations could be very beneficial.

Arrays of neutral-atom qubits in optical tweezers are a promising platform for quantum computation. Despite experimental progress, a major roadblock for realizing neutral-atom quantum computation is the qubit initialization. Here we propose that supersymmetry, a theoretical framework developed in particle physics, can be used for ultrahigh-fidelity initialization of neutral-atom qubits. We show that a single atom can be deterministically prepared in the vibrational ground state of an optical tweezer by adiabatically extracting all excited atoms to a supersymmetric auxiliary tweezer. The scheme works for both bosonic and fermionic atom qubits trapped in realistic Gaussian optical tweezers and may pave the way for realizing large-scale quantum computation, simulation, and information processing with neutral atoms.

Time-dependent drives hold promise for realizing non-equilibrium many-body phenomena that are absent in undriven systems1-3. Yet, drive-induced heating normally destabilizes the systems4,5, which can be parametrically suppressed in the high-frequency regime by using periodic (Floquet) drives6,7. It remains largely unknown to what extent highly controllable quantum simulators can suppress heating in non-periodically driven systems. Here, using the 78-qubit superconducting quantum processor, Chuang-tzu 2.0, we report the experimental observation of long-lived prethermal phases in many-body systems with tunable heating rates, driven by structured random protocols, characterized by n-multipolar temporal correlations. By measuring both the particle imbalance and subsystem entanglement entropy, we monitor the entire heating process over 1,000 driving cycles and observe the existence of the prethermal plateau. The prethermal lifetime is 'doubly tunable': one way by driving frequency, the other way by multipolar order; it grows algebraically with the frequency with the universal scaling exponent 2n+1. Using quantum-state tomography on different subsystems, we demonstrate a non-uniform spatial entanglement distribution and observe a crossover from area-law to volume-law entanglement scaling. With 78 qubits and 137 couplers in a two-dimensional configuration, the entire far-from-equilibrium heating dynamics are beyond the reach of simulation using tensor-network numerical techniques. Our work highlights superconducting quantum processors as a powerful platform for exploring universal scaling laws and non-equilibrium phases of matter in driven systems in regimes where classical simulation faces formidable challenges.

Many of the biggest challenges in expanding the nation’s access to clean and low-cost energy resources are fundamentally chemistry or materials challenges. An important case is the development of new catalysts for the up-conversion of cheap and readily available materials such as methane or water into materials suitable for use as a fuel such as methanol or oxygen. To understand and exploit such processes, computer simulations of chemical reactions provide a natural complement to experimental studies. Unfortunately, most catalytic reactions involve so-called “strongly correlated” molecules which are notoriously difficult to study with simulation algorithms that can be executed on existing (classical) computers. The recent growth in quantum information science offers an alternative potential route for simulating these difficult systems. As a result, an increasing number of computational chemists are becoming interested in quantum computing. At the same time, quantum information scientists have identified chemistry simulation as a possible first demonstration of a quantum computer providing an improvement over a classical computer. The objective of this project is to accurately simulate strongly correlated molecules on a quantum processor. To meet the high challenges of this objective, new hybrid quantum/classical algorithms will be co-designed with advanced quantum gate developments and computed on customized quantum hardware. Some of the developed techniques will be transferable to study other molecular systems, while the project as a whole will help define better strategies for advancing the quantum simulation of matter more generally.

Fermions are basic building blocks in the standard model. Interactions among these elementary particles determine how they assemble and consequently form various states of matter in our nature. Simulating fermionic degrees of freedom is also a central problem in condensed matter physics and quantum chemistry, which is crucial to understanding high-temperature superconductivity, quantum magnetism and molecular structure and functionality. However, simulating interacting fermions by classical computing generically face the minus sign problem, encountering the exponential computation complexity. Ultracold atoms provide an ideal experimental platform for quantum simulation of interacting fermions. This highly-controllable system enables the realizing of nontrivial fermionic models, by which the physical properties of the models can be obtained by measurements in experiment. This deepens our understanding of related physical mechanisms and helps determine the key parameters. In recent years, there have been versatile experimental studies on quantum ground state physics, finite temperature thermal equilibrium, and quantum many-body dynamics, in fermionic quantum simulation systems. Quantum simulation offers an access to the physical problems that are intractable on the classical computer, including studying macroscopic quantum phenomena and microscopic physical mechanisms, which demonstrates the quantum advantages of controllable quantum systems. This paper briefly introduces the model of interacting fermions describing the quantum states of matter in such a system. Then we discuss various states of matter, which can arise in interacting fermionic quantum systems, including Cooper pair superfluids and density-wave orders. These exotic quantum states play important roles in describing high-temperature superconductivity and quantum magnetism, but their simulations on the classical computers have exponentially computational cost. Related researches on quantum simulation of interacting fermions in determining the phase diagrams and equation of states reflect the quantum advantage of such systems.

Microcavity polaritons are hybrid quasiparticles emerging from the strong coupling between quantum well excitons and light in the resonator. Their unique half-light half-matter nature brings in specific properties like low effective mass, nonlinearity due to the repulsive interactions, and ability to directly access the polaritonic wavefunction through optical means. Due to their specific features, polaritons can form macroscopic quantum states and even undergo Bose-Einstein condensation, which makes them very interesting system for studying the quantum phenomena occurring on a macroscopic scale. This thesis is devoted to the investigation of dynamics of the second-order coherence of the microcavity polaritons. The evolution of the coherence of the polariton system occurs on a timescale of few picoseconds only, which required assembly of a new ultrafast photon correlation setup based on the streak-camera. The operation of this setup and requirements for high-quality measurements are discussed in details. After this, the experiments under both nonresonant and resonant excitation of polaritons are reported. Under nonresonant excitation, the formation of the polariton Bose-Einstein condensate is observed, and the change of the polariton coherence during this phase transition is measured. This indicates the time which is required to formthe condensate, and also allows to estimate its propagation velocity. The latter is compared with the measurements of the first-order spatial correlation function. Finally, polaritons confined in two coupled potential traps are studied. The traps are fabricated using the wet etching of the microcavity. In the resulting Josephson junction, polaritons are excited resonantly and demonstrate clear Josephson oscillations between the two traps. At the same time, the correlation measurements demonstrate strong perturbations of the light statistics in phase with the oscillations. This behavior is well represented with the quantum simulations, which also indicate presence of a significant quadrature squeezing in the system. The origin of the squeezing, the perspective for generating the nonclassical light, and other features of this phenomenon are discussed.