Twelve-qubit quantum computing for chemistry
Accurate electronic structure calculations are considered one of the most anticipated applications of quantum computing that will revolutionize ...theoretical chemistry and other related fields. Using the Google Sycamore quantum processor, Google AI Quantum and collaborators performed a variational quantum eigensolver (VQE) simulation of two intermediate-scale chemistry problems: the binding energy of hydrogen chains (as large as H
12
) and the isomerization mechanism of diazene (see the Perspective by Yuan). The simulations were performed on up to 12 qubits, involving up to 72 two-qubit gates, and show that it is possible to achieve chemical accuracy when VQE is combined with error mitigation strategies. The key building blocks of the proposed VQE algorithm are potentially scalable to larger systems that cannot be simulated classically.
Science
, this issue p.
1084
; see also p.
1054
Accurate quantum simulations of chemistry are performed using up to 12 superconducting qubits and 72 two-qubit gates.
The simulation of fermionic systems is among the most anticipated applications of quantum computing. We performed several quantum simulations of chemistry with up to one dozen qubits, including modeling the isomerization mechanism of diazene. We also demonstrated error-mitigation strategies based on
N
-representability that dramatically improve the effective fidelity of our experiments. Our parameterized ansatz circuits realized the Givens rotation approach to noninteracting fermion evolution, which we variationally optimized to prepare the Hartree-Fock wave function. This ubiquitous algorithmic primitive is classically tractable to simulate yet still generates highly entangled states over the computational basis, which allowed us to assess the performance of our hardware and establish a foundation for scaling up correlated quantum chemistry simulations.
Faster algorithms for combinatorial optimization could prove transformative for diverse areas such as logistics, finance and machine learning. Accordingly, the possibility of quantum enhanced ...optimization has driven much interest in quantum technologies. Here we demonstrate the application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algorithm (QAOA). Like past QAOA experiments, we study performance for problems defined on the planar connectivity graph native to our hardware; however, we also apply the QAOA to the Sherrington–Kirkpatrick model and MaxCut, non-native problems that require extensive compilation to implement. For hardware-native problems, which are classically efficient to solve on average, we obtain an approximation ratio that is independent of problem size and observe that performance increases with circuit depth. For problems requiring compilation, performance decreases with problem size. Circuits involving several thousand gates still present an advantage over random guessing but not over some efficient classical algorithms. Our results suggest that it will be challenging to scale near-term implementations of the QAOA for problems on non-native graphs. As these graphs are closer to real-world instances, we suggest more emphasis should be placed on such problems when using the QAOA to benchmark quantum processors.It is hoped that quantum computers may be faster than classical ones at solving optimization problems. Here the authors implement a quantum optimization algorithm over 23 qubits but find more limited performance when an optimization problem structure does not match the underlying hardware.
Realizing the potential of quantum computing requires sufficiently low logical error rates.sup.1. Many applications call for error rates as low as 10.sup.-15 (refs. .sup.2-9), but state-of-the-art ...quantum platforms typically have physical error rates near 10.sup.-3 (refs. .sup.10-14). Quantum error correction.sup.15-17 promises to bridge this divide by distributing quantum logical information across many physical qubits in such a way that errors can be detected and corrected. Errors on the encoded logical qubit state can be exponentially suppressed as the number of physical qubits grows, provided that the physical error rates are below a certain threshold and stable over the course of a computation. Here we implement one-dimensional repetition codes embedded in a two-dimensional grid of superconducting qubits that demonstrate exponential suppression of bit-flip or phase-flip errors, reducing logical error per round more than 100-fold when increasing the number of qubits from 5 to 21. Crucially, this error suppression is stable over 50 rounds of error correction. We also introduce a method for analysing error correlations with high precision, allowing us to characterize error locality while performing quantum error correction. Finally, we perform error detection with a small logical qubit using the 2D surface code on the same device.sup.18,19 and show that the results from both one- and two-dimensional codes agree with numerical simulations that use a simple depolarizing error model. These experimental demonstrations provide a foundation for building a scalable fault-tolerant quantum computer with superconducting qubits.
Information scrambling in quantum circuits Mi, Xiao; Roushan, Pedram; Quintana, Chris ...
Science (American Association for the Advancement of Science),
2021-Dec-17, 2021-12-17, 20211217, Letnik:
374, Številka:
6574
Journal Article
Recenzirano
Odprti dostop
Interactions in quantum systems can spread initially localized quantum information into the exponentially many degrees of freedom of the entire system. Understanding this process, known as quantum ...scrambling, is key to resolving several open questions in physics. Here, by measuring the time-dependent evolution and fluctuation of out-of-time-order correlators, we experimentally investigate the dynamics of quantum scrambling on a 53-qubit quantum processor. We engineer quantum circuits that distinguish operator spreading and operator entanglement and experimentally observe their respective signatures. We show that whereas operator spreading is captured by an efficient classical model, operator entanglement in idealized circuits requires exponentially scaled computational resources to simulate. These results open the path to studying complex and practically relevant physical observables with near-term quantum processors.
Niobium is one of the most studied superconductors, both theoretically and experimentally. It is tremendously important for applications, and it has the highest superconducting transition ...temperature, Tc = 9.32 K, of all pure metals. In addition to power applications in alloys, pure niobium is used for sensitive magnetosensing, radio-frequency cavities, and, more recently, as circuit metallization layers in superconducting qubits. A detailed understanding of its electronic and superconducting structure, especially its normal and superconducting state anisotropies, is crucial for mitigating the loss of quantum coherence in such devices. Recently, a microscopic theory of the anisotropic properties of niobium with the disorder was put forward. To verify theoretical predictions, we studied the effect of disorder produced by 3.5 MeV proton irradiation of thin Nb films grown by the same team and using the same protocols as those used in transmon qubits. By measuring the superconducting transition temperature and upper critical fields, we show a clear suppression of Tc by potential (nonmagnetic) scattering, which is directly related to the anisotropic order parameter. Here, we obtain a very close quantitative agreement between the theory and the experiment.
Niobium thin films on silicon substrate used in the fabrication of superconducting qubits have been characterized using scanning and transmission electron microscopy, electrical transport, ...magnetization, the London penetration depth - based quasiparticle spectroscopy, and real-space real-time magneto-optical imaging. Here we study niobium films to provide an example of a comprehensive analytical set that may benefit superconducting circuits such as those used in quantum computers. The films have a superconducting transition temperature of Tc = 9.35 K and a fairly clean superconducting gap. The estimated superfluid density is enhanced at intermediate temperatures. These observations are consistent with the recent theory of anisotropic strong-coupling superconductivity in Nb and indicate outstanding quality. However, the response to the magnetic field is complicated, exhibiting significantly irreversible behavior and insufficient heat dissipation (to a substrate), leading to thermomagnetic instabilities. This may present a challenge for further improvement of transmon quantum coherence. Possible mitigation strategies are discussed.
We devise a scheme to characterize tunneling of an excess electron shared by a pair of tunnel-coupled dangling bonds on a silicon surface-effectively a two-level system. Theoretical estimates show ...that the tunneling should be highly coherent but too fast to be measured by any conventional techniques. Our approach is instead to measure the time-averaged charge distribution of our dangling-bond pair by a capacitively coupled atomic-force-microscope tip in the presence of both a surface-parallel electrostatic potential bias between the two dangling bonds and a tunable midinfrared laser capable of inducing Rabi oscillations in the system. With a nonresonant laser, the time-averaged charge distribution in the dangling-bond pair is asymmetric as imposed by the bias. However, as the laser becomes resonant with the coherent electron tunneling in the biased pair the theory predicts that the time-averaged charge distribution becomes symmetric. This resonant symmetry effect should not only reveal the tunneling rate, but also the nature and rate of decoherence of single-electron dynamics in our system.
Abstract We present a transmon qubit fabrication technique that yields systematic improvements in T 1 relaxation times. We encapsulate the surface of niobium and prevent the formation of its lossy ...surface oxide. By maintaining the same superconducting metal and only varying the surface, this comparative investigation examining different capping materials, such as tantalum, aluminum, titanium nitride, and gold, as well as substrates across different qubit foundries demonstrates the detrimental impact that niobium oxides have on coherence times of superconducting qubits, compared to native oxides of tantalum, aluminum or titanium nitride. Our surface-encapsulated niobium qubit devices exhibit T 1 relaxation times 2–5 times longer than baseline qubit devices with native niobium oxides. When capping niobium with tantalum, we obtain median qubit lifetimes above 300 μs, with maximum values up to 600 μs. Our comparative structural and chemical analysis provides insight into why amorphous niobium oxides may induce higher losses compared to other amorphous oxides.
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