Author(s): Qingxiuxiong Dong, Marco Túlio Quintino, Akihito Soeda, and Mio Murao

The repeat-until-success strategy is a standard method to obtain success with a probability that grows exponentially with the number of iterations. However, since quantum systems are disturbed after a quantum measurement, how to perform repeat-until-success strategies in certain quantum algorithms i...

[Phys. Rev. Lett. 126, 150504] Published Fri Apr 16, 2021

Author(s): Katherine Wright

Two research teams have used eye-tracking methods to learn how students approach complex physics problems.

[Physics 14, 59] Published Fri Apr 16, 2021

Categories: Physics

We analyze the conclusions of the influence of a Coulomb-type potential on the Klein-Gordon oscillator. We show that the truncation method proposed by the authors do not yield all the eigenvalues of the radial equation but just one of them for a particular value of a model parameter. Besides, the existence of allowed oscillator frequencies that depend on the quantum numbers is an artifact of the truncation method.

In the current era of Noisy Intermediate-Scale Quantum (NISQ) technology, the practical use of quantum computers remains inhibited by our inability to aptly decouple qubits from their environment to mitigate computational errors. In this work, we introduce an approach by which knowledge of a qubit's initial quantum state and the standard parameters describing its decoherence can be leveraged to mitigate the noise present during the execution of a single-qubit gate. We benchmark our protocol using cloud-based access to IBM quantum processors. On ibmq_rome, we demonstrate a reduction of the single-qubit error rate by $38\%$, from $1.6 \times 10 ^{-3}$ to $1.0 \times 10 ^{-3}$, provided the initial state of the input qubit is known. On ibmq_bogota, we prove that our protocol will never decrease gate fidelity, provided the system's $T_1$ and $T_2$ times have not drifted above $100$ times their assumed values. The protocol can be used to reduce quantum state preparation errors, as well as to improve the fidelity of quantum circuits for which some knowledge of the qubits' intermediate states can be inferred. This work presents a pathway to using information about noise levels and quantum state distributions to significantly reduce error rates associated with quantum gates via optimized decomposition into native gates.

Although gauge invariance is a postulate in fundamental theories of nature such as quantum electrodynamics, in quantum-simulation implementations of gauge theories it is compromised by experimental imperfections. In a recent work [Halimeh and Hauke, \href{https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.125.030503}{Phys. Rev. Lett. \textbf{125}, 030503 (2020)}], it has been shown in finite-size spin-$1/2$ quantum link lattice gauge theories that upon introducing an energy-penalty term of sufficiently large strength $V$, unitary gauge-breaking errors at strength $\lambda$ are suppressed $\propto\lambda^2/V^2$ up to all accessible evolution times. Here, we show numerically that this result extends to quantum link models in the thermodynamic limit and with larger spin-$S$. As we show analytically, the dynamics at short times is described by an \textit{adjusted} gauge theory up to a timescale that is at earliest $\tau_\text{adj}\propto\sqrt{V/V_0^3}$, with $V_0$ an energy factor. Moreover, our analytics predicts that a renormalized gauge theory dominates at intermediate times up to a timescale $\tau_\text{ren}\propto\exp(V/V_0)/V_0$. In both emergent gauge theories, $V$ is volume-independent and scales at worst $\sim S^2$. Furthermore, we numerically demonstrate that robust gauge invariance is also retained through a single-body gauge-protection term, which is experimentally straightforward to implement in ultracold-atom setups and NISQ devices.

It is pointed out that the solutions of the Klein-Gordon and the Dirac equation derived in the paper addressed in this Comment (and many more solutions) may be obtained from generating functions.

The realization of a functional quantum repeater is one of the major research goals in long-distance quantum communication. Among the different approaches that are being followed, the one relying on quantum memories interfaced with deterministic quantum emitters is considered as among one of the most promising solutions. In this work, we focus on memory-based quantum-repeater schemes that rely on semiconductor quantum dots for the generation of polarization entangled photons. Going through the most relevant figures of merit related to efficiency of the photon source, we select significant developments in fabrication, processing and tuning techniques aimed at combining high degree of entanglement with on-demand pair generation, with a special focus on the progress achieved in the representative case of the GaAs system. We proceed to offer a perspective on integration with quantum memories, both highlighting preliminary works on natural-artificial atomic interfaces and commenting a wide choice of currently available and potentially viable memory solutions in terms of wavelength, bandwidth and noise-requirements. To complete the overview, we also present recent implementations of entanglement-based quantum communication protocols with quantum dots and highlight the next challenges ahead for the implementation of practical quantum networks.

We demonstrate super-resolution optical sensing of the size of the wave packet of a single trapped ion. Our method is inspired by the well known ground state depletion (GSD) technique. Here, we use a hollow beam to strongly saturate a dipole-forbidden transition around a sub-diffraction limited area at its center and observe state dependent fluorescence. By spatially scanning this laser beam over a single trapped $^{40}\mathrm{Ca}^+$ ion, we are able to distinguish the wave packet sizes of ions cooled to different temperatures. Using a depletion beam waist of $4.2(1)\,\mu$m we reach a spatial resolution which allows us to determine a wave packet size of $39(9)\,$nm for a near ground state cooled ion. This value matches an independently deduced value of $32(2)\,$nm, calculated from resolved sideband spectroscopy measurements. Finally, we discuss the ultimate resolution limits of our adapted GSD imaging technique in the view of applications to direct quantum wave packet imaging.

The early definition of a quantum neural network as a new field that combines the classical neurocomputing with quantum computing was rather vague and satisfactory in the 2000s. The widespread in 2020 modern definition of a quantum neural network as a model or machine learning algorithm that combines the functions of quantum computing with artificial neural networks deprives quantum neural networks of their fundamental importance. We argue that the concept of a quantum neural network should be defined in terms of its most general function as a tool for representing the amplitude of an arbitrary quantum process. Our reasoning is based on the use of the Feynman path integral formulation in quantum mechanics. This approach has been used in many works to investigate the main problem of quantum cosmology, such as the origin of the Universe. In fact, the question of whether our Universe is a quantum computer was posed by Seth Lloyd, who gave the answer is yes, but we argue that the universe can be thought of as a quantum neural network.

With optimal control theory, we compute the maximum possible quantum Fisher information about the interaction parameter for a Kitaev chain with tunable long-range interactions in the many-particle Hilbert space. We consider a wide class of decay laws for the long-range interaction and develop rigorous asymptotic analysis for the scaling of the quantum Fisher information with respect to the number of lattice sites. In quantum metrology nonlinear many-body interactions can enhance the precision of quantum parameter estimation to surpass the Heisenberg scaling, which is quadratic in the number of lattice sites. Here for the estimation of the long-range interaction strength, we observe the Heisenberg to super-Heisenberg transition in such a $linear$ model, related to the slow decaying long-range correlations in the model. Finally, we show that quantum control is able to improve the prefactor rather than the scaling exponent of the quantum Fisher information. This is in contrast with the case where quantum control has been shown to improve the scaling of quantum Fisher information with the probe time. Our results clarify the role of quantum controls and long-range interactions in many-body quantum metrology.

In quantum coherent systems, it is impossible to measure the work distribution without affecting the thermodynamic process itself. This is a fundamental issue and any attempt to overcome it will necessarily have shortcomings, such as negative probabilities. In this letter we show how this conundrum can be avoided by introducing the notion of predictor of work. Given stochastic outcomes for the heat exchanged with the environment (which can be measured non-invasively), the predictor is a mapping providing a guess for work involved. Using quantum Bayesian networks, we show how one can construct the optimal predictor in the mean-squared sense. Our framework casts the determination of the work distribution as a problem in statistical inference, which can be directly connected to experimental methods, as we illustrate by considering a qubit subject to an avoided crossing work protocol. As a non-trivial application, we also analyze a coherent version of the Scovil and Schulz-DuBois 3-level engine.

Nonadiabatic molecular dynamics occur in a wide range of chemical reactions and femtochemistry experiments involving electronically excited states. These dynamics are hard to treat numerically as the system's complexity increases and it is thus desirable to have accurate yet affordable methods for their simulation. Here, we introduce a linearized semiclassical method, the generalized discrete truncated Wigner approximation (GDTWA), which is well-established in the context of quantum spin lattice systems, into the arena of chemical nonadiabatic systems. In contrast to traditional continuous mapping approaches, e.g. the Meyer-Miller-Stock-Thoss and the spin mappings, GDTWA samples the electron degrees of freedom in a discrete phase space, and thus forbids an unphysical unbounded growth of electronic state populations. The discrete sampling also accounts for an effective reduced but non-vanishing zero-point energy without an explicit parameter, which makes it possible to treat the identity operator and other operators on an equal footing. As numerical benchmarks on two Linear Vibronic Coupling models show, GDTWA has a satisfactory accuracy in a wide parameter regime, independently of whether the dynamics is dominated by relaxation or by coherent interactions. Our results suggest that the method can be very adequate to treat challenging nonadiabatic dynamics problems in chemistry and related fields.

Single-molecule memory device based on a single-molecule magnet (SMM) is one of the ultimate goals of semiconductor nanofabrication technologies. Here, we study how to manipulate and readout the SMM's spin states of stored information that characterized by the maximum and minimum average value of the $Z$-component of the SMM's spin, which are recognized as the information bits "1" and "0". We demonstrate that the switching time depends on both the sequential tunneling gap $\varepsilon_{se}$ and the spin-selection-role allowed transition-energy $\varepsilon_{trans}$, which can be tuned by the gate voltage. In particular, when the external bias voltage is turned off, in the cases of the empty-occupied and doubly-occupied ground eigenstates, the time derivative of the transport current and that of the average value of the SMM's spin states can be used to read out the SMM's spin states of stored information. Moreover, the tunneling strength of and the asymmetry of SMM-electrode coupling have a strong influence on the switching time, but that have a slight influence on the readout time that being on the order of nanoseconds. Our results suggest a SMM-based memory device, and provide fundamental insight into the electrical controllable manipulation and readout of the SMM's spin-state of stored information.

We discuss the non-Abelian artificial magnetic monopoles associated with $n$-level energy crossing in quantum systems. We found that hidden symmetries reveal themselves as observables such as spin, charge, and other physical degrees of freedom. We illustrated our results on concrete examples of two and three energy-level crossing. Our results can be useful for modeling of various phenomena in physical and biological systems.

Currently there are three major paradigms of quantum computation, the gate model, annealing, and walks on graphs. The gate model and quantum walks on graphs are universal computation models, while annealing plays within a specific subset of scientific and numerical computations. Quantum walks on graphs have, however, not received such widespread attention and thus the door is wide open for new applications and algorithms to emerge. In this paper we explore teaching a coined discrete time quantum walk on a regular graph a probability distribution. We go through this exercise in two ways. First we adjust the angles in the maximal torus $\mathbb{T}^d$ where $d$ is the regularity of the graph. Second, we adjust the parameters of the basis of the Lie algebra $\mathfrak{su}(d)$. We also discuss some hardware and software concerns as well as immediate applications and the several connections to machine learning.

Collective strong coupling between a disordered ensemble of $N$ localized molecular vibrations and a resonant optical cavity mode gives rise to 2 polariton and $N-1\gg2$ dark modes. Thus, experimental changes in thermally-activated reaction kinetics due to polariton formation appear entropically unlikely and remain a puzzle. Here we show that the overlooked dark modes, while parked at the same energy as bare molecular vibrations, are robustly delocalized across $\sim$2-3 molecules, yielding enhanced channels of vibrational cooling, concomitantly catalyzing or suppressing a chemical reaction. As an illustration, we theoretically show a 55% increase in an electron transfer rate due to enhanced product stabilization.

A foundational question in quantum computational complexity asks how much more useful a quantum state can be in a given task than a comparable, classical string. Aaronson and Kuperberg showed such a separation in the presence of a quantum oracle, a black box unitary callable during quantum computation. Their quantum oracle responds to a random, marked, quantum state, which is intractable to specify classically. We constrain the marked state in ways that make it easy to specify classically while retaining separations in task complexity. Our method replaces query by state complexity. Furthermore, assuming a widely believed separation between the difficulty of creating a random, complex state and creating a specified state, we propose an experimental demonstration of quantum witness advantage on near-term, distributed quantum computers. Finally, using the fact that a standard, classically defined oracle may enable a quantum algorithm to prepare an otherwise hard state in polynomial steps, we observe quantum-classical oracle separation in heavy output sampling.

Bounding the cost of classically simulating the outcomes of universal quantum circuits to additive error $\delta$ is often called weak simulation and is a direct way to determine when they confer a quantum advantage. Weak simulation of the $T$+Clifford gateset is $BQP$-complete and is expected to scale exponentially with the number $t$ of $T$ gates. We constructively tighten the upper bound on the worst-case $L_1$ norm sampling cost to next order in $t$ from $\mathcal O(\xi^t \delta^{-2})$ to $\mathcal O((\xi^t{-}\frac{2{-}\sqrt{2}}{2} t)\delta^{-2})$, where $\xi^t = 2^{\sim 0.228 t}$ is the stabilizer extent of the $t$-tensored $T$ gate magic state. We accomplish this by replacing independent $L_1$ sampling in the popular SPARSIFY algorithm used in many weak simulators with correlated $L_1$ sampling. As an aside, this result demonstrates that the minimal $L_1$ stabilizer state norm's dependence on $t$ for finite values is not multiplicative, despite the multiplicativity of its stabilizer extent. This is the first weak simulation algorithm that has lowered this bound's dependence on finite $t$ in the worst-case to our knowledge and establishes how to obtain further such reductions in $t$.

We find out a cone program for getting entanglement breaking channels as outputs of interpolation problem. Afterward, we generalize our results for getting channels that belong to a convex set as outputs of the interpolation problem.

The interplay between the spin-orbit and Zeeman interactions on a spinful Su-Schrieffer-Heeger model is studied based on an InAs nanowire subjected to a periodic gate potential along the axial direction. It is shown that a nontrivial topological phase can be achieved by regulating the confining-potential configuration. In the absence of the Zeeman field, we prove that the topology of the chain is not affected by the Rashba spin-orbit interaction due to the persisting chiral symmetry. The energies of the edge modes can be manipulated by varying the magnitude and direction of the external magnetic field.Remarkably, the joint effect of the two spin-related interactions leads to novel edge states that appear in the gap formed below the anti-crossing of the bands of an open spinful dimerized chain, and can be merged into the bulk states by tilting the magnetic-field direction.