Quantum Physics (quant-ph)

Abstract: The primary objective of quantum Shannon theory is to evaluate the capacity of quantum channels, which is a challenging task in many instances. Recently, Multi-level Amplitude Damping channel has been introduced, and the corresponding quantum capacity of the channel has been analyzed for a quantum system of dimension d=3 [S. Chessa, V. Giovannetti, Commun. Phys. 4,22 (2021)]. In this paper, we have investigated the information capacity of Multi-level Amplitude Damping Channel for dimension d=3 in presence of correlation between successive applications of the channel. We derive the single-shot classical capacities and quantum capacities associated with a different class of maps for the three-level system. Additionally, we compute the quantum and classical capacities in entanglement-assisted scenarios.

Abstract: In this paper, we propose a framework to study the combined effect of several factors that contribute to the barren plateau problem in quantum neural networks (QNNs), which is a critical challenge in quantum machine learning (QML). These factors include data encoding, qubit entanglement, and ansatz expressibility. To investigate this joint effect in a real-world context, we focus on hybrid quantum neural networks (HQNNs) for multi-class classification. Our proposed framework aims to analyze the impact of these factors on the training landscape of HQNNs. Our findings show that the barren plateau problem in HQNNs is dependent on the expressibility of the underlying ansatz and the type of data encoding. Furthermore, we observe that entanglement also plays a role in the barren plateau problem. By evaluating the performance of HQNNs with various evaluation metrics for classification tasks, we provide recommendations for different constraint scenarios, highlighting the significance of our framework for the practical success of QNNs.

Abstract: We argue that, in the quest for the translation of fundamental research into actual quantum technologies, two avenues that have - so far - only partly explored should be pursued vigorously. On first entails that the study of energetics at the fundamental quantum level holds the promises for the design of a generation of more energy-efficient quantum devices. On second route to pursue implies a more structural hybridisation of quantum dynamics with data science techniques and tools, for a more powerful framework for quantum information processing.

Abstract: Adaptive tomography has been widely investigated to achieve faster state tomography processing of quantum systems. Infidelity of the nearly pure states in a quantum information process generally scales as O(1/sqrt(N) ), which requires a large number of statistical ensembles in comparison to the infidelity scaling of O(1/N) for mixed states. One previous report optimized the measurement basis in a photonic qubit system, whose state tomography uses projective measurements, to obtain an infidelity scaling of O(1/N). However, this dramatic improvement cannot be applied to weak-value-based measurement systems in which two quantum states cannot be distinguished with perfect measurement fidelity. We introduce in this work a new optimal measurement basis to achieve fast adaptive quantum state tomography and a minimum magnitude of infidelity in a weak measurement system. We expect that the adaptive quantum state tomography protocol can lead to a reduction in the number of required measurements of approximately 33.74% via simulation without changing the O(1/sqrt(N)) scaling. Experimentally, we find a 14.81% measurement number reduction in a superconducting circuit system.

Abstract: Ground-state preparation is an important task in quantum computation. The probabilistic imaginary-time evolution (PITE) method is a promising candidate for preparing the ground state of the Hamiltonian, which comprises a single ancilla qubit and forward- and backward-controlled real-time evolution operators. Here, we analyze the computational costs of the PITE method for both linear and exponential scheduling of the imaginary-time step size. First, we analytically discuss an error defined as the closeness between the states acted on by exact and approximate imaginary-time evolution operators. The optimal imaginary-time step size and speed of change of imaginary time were also discussed. Subsequently, the analytical discussion was verified using numerical simulations for a one-dimensional Heisenberg chain. As a result, we conclude that exponential scheduling with slow changes is preferable for reducing the computational costs.

Abstract: We explore a full dynamical phase diagram by means of a double quench protocol that depends on a relaxation time as the only control parameter. The protocol comprises two fixed quenches and an intermediate relaxation time that determines the phase in which the quantum state is placed after the final quench. We apply it to an anharmonic Lipkin-Meshkov-Glick model. This model displays two excited-state quantum phase transitions which split the spectrum into three different phases: two of them are symmetry-breaking phases, and one is a disordered phase. As a consequence, our protocol induces several kind of dynamical phase transitions. We characterize all of them in terms of the constants of motion characterizing all three phases of the model.

Abstract: The Fermi-Hubbard model is one of the central paradigms in the physics of strongly-correlated quantum many-body systems. Here we propose a quantum circuit algorithm based on the $\mathrm{Z}_2$ lattice gauge theory (LGT) representation of the one-dimensional Fermi-Hubbard model, which is suitable for implementation on current NISQ quantum computers. Within the LGT description there is an extensive number of local conserved quantities commuting with the Hamiltonian. We show how these conservation laws can be used to implement an efficient error-mitigation scheme. The latter is based on a post-selection of states for noisy quantum simulators. While the LGT description requires a deeper quantum-circuit compared to a Jordan-Wigner (JW) based approach, remarkably, we find that our error-correction protocol leads to results being on-par or even better than a standard JW implementation on noisy quantum simulators.

Abstract: Three classes of entangled coherent states are employed to study the Bell-CHSH inequality. By using pseudospin operators in infinite dimensional Hilbert spaces, four dichotomic operators $(A,A',B,B')$ entering the inequality are constructed. For each class of coherent states, we compute the correlator $\langle \psi \vert A B + A' B + A B' - A' B' \vert \psi \rangle$, analyzing the set of parameters that leads to a Bell-CHSH inequality violation and, particularly, to the saturation of Tsirelson's bound.

Abstract: A crucial task to obtain optimal and reliable quantum devices is to quantify their overall performance. The average fidelity of quantum gates is a particular figure of merit that can be estimated efficiently by Randomized Benchmarking (RB). However, the concept of gate-fidelity itself relies on the crucial assumption that noise behaves in a predictable, time-local, or so-called Markovian manner, whose breakdown can naturally become the leading source of errors as quantum devices scale in size and depth. We analytically show that error suppression techniques such as Dynamical Decoupling (DD) and Randomized Compiling (RC) can operationally Markovianize RB: i) fast DD reduces non-Markovian RB to an exponential decay plus longer-time corrections, while on the other hand, ii) RC generally does not affect the average, but iii) it always suppresses the variance of such RB outputs. We demonstrate these effects numerically with a qubit noise model. Our results show that simple and efficient error suppression methods can simultaneously tame non-Markovian noise and allow for standard and reliable gate quality estimation, a fundamentally important task in the path toward fully functional quantum devices.

Abstract: Oracle quantum state preparation is a variant of quantum state preparation where we want to construct a state $|\psi_c\rangle \propto \sum_x c(x) |x\rangle$ with the amplitudes $c(x)$ given as a (quantum) oracle. This variant is particularly useful when the quantum state has a short and simple classical description. We use recent techniques, namely quantum signal processing (QSP) and quantum singular value transform (QSVT), to construct a new algorithm that uses a polynomial number of qubits and oracle calls to construct $|\psi_c\rangle$. For a large class of states, this translates to an algorithm that is polynomial in the number of qubits, both in depth and width.

Abstract: The Schr\"odinger equation predicts the validity of the superposition principle at any scale, yet we do not experience cats being in a superposition of "dead" and "alive" in our everyday lives. Modifications to quantum theory at the fundamental level may be responsible for the objective collapse of the wave function above a critical mass, thereby breaking down the superposition principle and restoring classical behavior at the macroscopic scale. One possibility is that these modifications are related to gravity, as described by the Di\'osi-Penrose wavefunction collapse model. Here, we investigate this model using experimental measurements on the decoherence of a Schr\"odinger cat state of a mechanical resonator with an effective mass of 16 micrograms.

Abstract: The recent developments of quantum computing present potential novel pathways for quantum chemistry, as the increased computational power of quantum computers could be harnessed to naturally encode and solve electronic structure problems. Theoretically exact quantum algorithms for chemistry have been proposed (e.g. Quantum Phase Estimation) but the limited capabilities of current noisy intermediate scale quantum devices (NISQ) motivated the development of less demanding hybrid algorithms. In this context, the Variational Quantum Eigensolver (VQE) algorithm was successfully introduced as an effective method to compute the ground state energy of small molecules. The current study investigates the Folded Spectrum (FS) method as an extension to the VQE algorithm for the computation of molecular excited states. It provides the possibility of directly computing excited states around a selected target energy, using the same ansatz as for the ground state calculation. Inspired by the variance-based methods from the Quantum Monte Carlo literature, the FS method minimizes the energy variance, thus requiring a computationally expensive squared Hamiltonian. We alleviate this potentially poor scaling by employing a Pauli grouping procedure, identifying sets of commuting Pauli strings that can be evaluated simultaneously. This allows for a significant reduction of the computational cost. We apply the FS-VQE method to small molecules (H$_2$,LiH), obtaining all electronic excited states with chemical accuracy on ideal quantum simulators.

Abstract: We review the staircase algorithm to decompose the exponential of a generalized Pauli matrix and we propose two alternative recursive methods which offer more efficient quantum circuits. The first algorithm we propose, defined as the inverted staircase algorithm, is more efficient in comparison to the standard staircase algorithm in the number of one-qubit gates, giving a polynomial improvement of n/2. For our second algorithm, we introduce fermionic SWAP quantum gates and a systematic way of generalizing these. Such fermionic gates offer a simplification of the number of quantum gates, in particular of CNOT gates, in most quantum circuits. Regarding the staircase algorithm, fermionic quantum gates reduce the number of CNOT gates in roughly n/2 for a large number of qubits. In the end, we discuss the difference between the probability outcomes of fermionic and non-fermionic gates and show that, in general, due to interference, one cannot substitute fermionic gates through non-fermionic gates without altering the outcome of the circuit.

Abstract: Photonic qubits play an instrumental role in the development of advanced quantum technolo- gies, including quantum networking, boson sampling and measurement based quantum computing. A promising framework for the deterministic production of indistinguishable single photons is an atomic emitter coupled to a single mode of a high finesse optical cavity. Polarisation control is an important cornerstone, particularly when the polarisation defines the state of a quantum bit. Here, we propose a scheme for producing bursts of polarised single photons by coupling a generalised atomic emitter to an optical cavity, exploiting a particular choice of quantisation axis. In connection with two re-preparation methods, simulations predict 10-photon bursts coincidence count rates on the order of 1 kHz with single 87Rb atoms trapped in a state of the art optical cavity. This paves the way for novel n-photon experiments with atom-cavity sources.

Abstract: Phase estimation, due to Kitaev [arXiv'95], is one of the most fundamental subroutines in quantum computing. In the basic scenario, one is given black-box access to a unitary $U$, and an eigenstate $\lvert \psi \rangle$ of $U$ with unknown eigenvalue $e^{i\theta}$, and the task is to estimate the eigenphase $\theta$ within $\pm\delta$, with high probability. The cost of an algorithm for us will be the number of applications of $U$ and $U^{-1}$. We tightly characterize the cost of several variants of phase estimation where we are no longer given an arbitrary eigenstate, but are required to estimate the maximum eigenphase of $U$, aided by advice in the form of states (or a unitary preparing those states) which are promised to have at least a certain overlap $\gamma$ with the top eigenspace. We give algorithms and matching lower bounds (up to logarithmic factors) for all ranges of parameters. We show that a small number of copies of the advice state (or of an advice-preparing unitary) are not significantly better than having no advice at all. We also show that having lots of advice (applications of the advice-preparing unitary) does not significantly reduce cost, and neither does knowledge of the eigenbasis of $U$. As an immediate consequence we obtain a lower bound on the complexity of the Unitary recurrence time problem, matching an upper bound of She and Yuen~[ITCS'23] and resolving one of their open questions. Lastly, we show that a phase-estimation algorithm with precision $\delta$ and error probability $\epsilon$ has cost $\Omega\left(\frac{1}{\delta}\log\frac{1}{\epsilon}\right)$, matching an easy upper bound. This contrasts with some other scenarios in quantum computing (e.g., search) where error-reduction costs only a factor $O(\sqrt{\log(1/\epsilon)})$. Our lower bound technique uses a variant of the polynomial method with trigonometric polynomials.