Quantum Physics (quant-ph)

Abstract: Quantum state transfer (QST) through spin chains has been extensively investigated. Two schemes, the coupling set for perfect state transfer (PST) or adding a leakage elimination operator (LEO) Hamiltonian have been proposed to boost the transmission fidelity. However, these ideal schemes are only suitable for closed systems and will lose their effectiveness in open ones. In this work, we invoke a well explored optimization algorithm, Adam, to expand the applicable range of PST couplings and LEO to the open systems. Our results show that although the transmission fidelity decreases with increasing system-bath coupling strength, Markovianity and temperature for both ideal and optimized cases, the fidelities obtained by the optimized schemes always outweigh the ideal cases. The enhancement becomes more bigger for a stronger bath, indicating a stronger bath provides more space for the Adam to optimize. This method will be useful for the realization of high-fidelity information transfer in the presence of environment.

Abstract: We propose a scheme for preparing magnon squeezed states in a hybrid cavity-magnon-qubit system. The system consists of a microwave cavity that simultaneously couples to a magnon mode of a macroscopic yttrium-iron-garnet (YIG) sphere via the magnetic-dipole interaction and to a transmon-type superconducting qubit via the electric-dipole interaction. By far detuning from the magnon-qubit system, the microwave cavity is adiabatically eliminated. The magnon mode and the qubit then get effectively coupled via the mediation of virtual photons of the microwave cavity. We show that by driving the qubit with two microwave fields and by appropriately choosing the drive frequencies and strengths, magnonic parametric amplification can be realized, which leads to magnon quadrature squeezing with the noise below vacuum fluctuation. We provide optimal conditions for achieving magnon squeezing, and moderate squeezing can be obtained using currently available parameters. The generated squeezed states are of a magnon mode involving more than $10^{18}$ spins and thus macroscopic quantum states. The work may find promising applications in quantum information processing and high-precision measurements based on magnons and in the study of macroscopic quantum states.

Abstract: DNA sequencing allows for the determination of the genetic code of an organism, and therefore is an indispensable tool that has applications in Medicine, Life Sciences, Evolutionary Biology, Food Sciences and Technology, and Agriculture. In this paper, we present several novel methods of performing classical-to-quantum data encoding inspired by various mathematical fields, and we demonstrate these ideas within Bioinformatics. In particular, we introduce algorithms that draw inspiration from diverse fields such as Electrical and Electronic Engineering, Information Theory, Differential Geometry, and Neural Network architectures. We provide a complete overview of the existing data encoding schemes and show how to use them in Genomics. The algorithms provided utilise lossless compression, wavelet-based encoding, and information entropy. Moreover, we propose a contemporary method for testing encoded DNA sequences using Quantum Boltzmann Machines. To evaluate the effectiveness of our algorithms, we discuss a potential dataset that serves as a sandbox environment for testing against real-world scenarios. Our research contributes to developing classical-to-quantum data encoding methods in the science of Bioinformatics by introducing innovative algorithms that utilise diverse fields and advanced techniques. Our findings offer insights into the potential of Quantum Computing in Bioinformatics and have implications for future research in this area.

Abstract: Devising efficient communication in a network consisting of multiple transmitters and receivers is a problem of immense importance in communication theory. Interestingly, resources in the quantum world have been shown to be very effective in enhancing the performance of communication networks. In this work, we study entanglement-assisted communication over classical network channels. When there is asymmetry such that noise introduced by the channel depends on the input alphabets, non communicating senders may exploit shared entangled states to overcome the noise. We consider multiple access channels, an essential building block for many complex networks, and develop an extensive framework for n-senders and 1-receiver multiple access channels based on nonlocal games. We obtain generic results for computing correlation assisted sum-capacities of these channels. The considered channels introduce less noise on winning and more noise on losing the game, and the correlation assistance is classified as local (L), quantum (Q), or no-signaling (NS). Furthermore, we consider a broad class of multiple access channels such as depolarizing ones that admix a uniform noise with some probability and prove general results on their sum-capacities. Finally, we apply our analysis to three specific depolarizing multiple access channels based on Clauser-Horne-Shimony-Holt, magic square, and Mermin-GHZ nonlocal games. In all three cases we find significant enhancements in sum-capacities on using nonlocal correlations. We obtain either exact expressions for sum-capacities or suitable upper and lower bounds on them. The general framework developed in this work has much wider applicability and the specificity studied in details are some illustrative examples to compare with recent studies in this direction.

Abstract: Quantum and quantum-inspired machine learning has emerged as a promising and challenging research field due to the increased popularity of quantum computing, especially with near-term devices. Theoretical contributions point toward generative modeling as a promising direction to realize the first examples of real-world quantum advantages from these technologies. A few empirical studies also demonstrate such potential, especially when considering quantum-inspired models based on tensor networks. In this work, we apply tensor-network-based generative models to the problem of molecular discovery. In our approach, we utilize two small molecular datasets: a subset of $4989$ molecules from the QM9 dataset and a small in-house dataset of $516$ validated antioxidants from TotalEnergies. We compare several tensor network models against a generative adversarial network using different sample-based metrics, which reflect their learning performances on each task, and multiobjective performances using $3$ relevant molecular metrics per task. We also combined the output of the models and demonstrate empirically that such a combination can be beneficial, advocating for the unification of classical and quantum(-inspired) generative learning.

Abstract: Several central problems in quantum information theory (such as measurement compatibility and quantum steering) can be rephrased as membership in the minimal matrix convex set corresponding to special polytopes (such as the hypercube or its dual). In this article, we generalize this idea and introduce the notion of polytope compatibility, by considering arbitrary polytopes. We find that semiclassical magic squares correspond to Birkhoff polytope compatibility. In general, we prove that polytope compatibility is in one-to-one correspondence with measurement compatibility, when the measurements have some elements in common and the post-processing of the joint measurement is restricted. Finally, we consider how much tuples operators with appropriate joint numerical range have to be scaled in the worst case in order to become polytope compatible and give both analytical sufficient conditions and numerical ones based on linear programming.

Abstract: The thermoelectric performance at a given output power of a voltage-probe heat engine, exposed to an external magnetic field, is investigated in linear irreversible thermodynamics. For the model, asymmetric parameter, general figures of merit and efficiency at a given output power are analytically derived. Results show a trade-off between efficiency and output power, and we recognize optimum-efficiency values at a given output power are enhanced compared to a B\"uttiker-probe heat engine due to the presence of a characteristic parameter, namely $d_m$. Moreover, similar to a B\"uttiker-probe heat engine, the universal bounds on the efficiency are obtained, and the efficiency at a given output power can exceed the Curzon-Ahlborn limit. These findings have practical implications for the optimization of realistic heat engines and refrigerators. By controlling the values of the asymmetric parameter, the figures of merit, and $d_m$, it may be possible to design more efficient and powerful thermoelectric devices.

Abstract: Multipartite quantum states constitute the key resource for quantum computation. The understanding of their internal structure is thus of great importance in the field of quantum information. This paper aims at examining the structure of multipartite maximally entangled pure states, using tools with a simple and intuitive physical meaning, namely, projective measurements and correlations. We first show how, in such states, a very simple relation arises between post-measurement expectation values and pre-measurement correlations. We then infer the consequences of this relation on the structure of the recently introduced \textit{entanglement metric}, allowing us to provide an upper bound for the \textit{persistency of entanglement}. The dependence of these features on the chosen measurement axis is underlined, and two simple optimization procedures are proposed, to find those maximizing the correlations. Finally, we apply our procedures onto some prototypical examples.

Abstract: Quantum state estimation (or state tomography) is an indispensable task in quantum information processing. Because full state tomography that determines all elements of the density matrix is computationally demanding, one usually takes the strategy of assuming a certain model of quantum states and identifying the model parameters. However, it is difficult to make a valid assumption given little prior knowledge on a quantum state of interest, and thus we need a reasonable model selection method for quantum state estimation. Actually, in the classical statistical estimation theory, several types of information criteria have been established and widely used in practice for appropriately choosing a classical statistical model. In this study, we propose quantum information criteria for evaluating the quality of the estimated quantum state in terms of the quantum relative entropy, which is a natural quantum analogue of the classical information criterion defined in terms of Kullback-Leibler divergence. In particular, we derive two quantum information criteria depending on the type of estimator for the quantum relative entropy; one uses the log-likelihood and the other uses the classical shadow. The general role of information criteria is to predict the performance of an estimated model for unseen data, although it is a function of only sampled data; this generalization capability of the proposed quantum information criteria is evaluated in numerical simulations.

Abstract: Graph states are entangled states useful for several quantum information processing tasks such as measurement-based quantum computation and quantum metrology. As the size of graph states realized in experiments increases, it becomes more essential to devise efficient methods estimating the fidelity between the ideal graph state and an experimentally-realized actual state. Any efficient fidelity-estimation method, in general, must use multiple experimental settings, i.e., needs to switch between at least two measurements. Recently, it has been shown that a single measurement is sufficient if the noise can be modeled as the phase-flip error. Since the bit-flip error should also occur in several experiments, it is desired to extend this simplest method to noise models that include phase and bit-flip errors. However, it seems to be nontrivial because their result strongly depends on properties of the phase-flip error. In this paper, by analyzing effects of the bit-flip error on stabilizer operators of graph states, we achieve the extension to the depolarizing noise, which is a major noise model including phase and bit-flip errors. We also numerically evaluate our simplest method for noise models interpolating between the phase-flip and depolarizing noises.

Abstract: Processing large amounts of data to this day causes difficulties due to the lack of power resources. Classical algorithms implement a chain of actions, requiring a certain time to execute, as well as space in the form of RAM. Parallelization, if it can be used, allows to gain time, but also needs buffering of all parallel actions. Quantum computing acts as an attractive alternative to parallel computing with qubits, qudits and their distinctive properties. The quantum algorithm proposed in this paper allows to search for the best (closest to a given) element in a random data array by storing all its initial elements in a superposition. This allows to perform the search operations on all elements at the same time and due to the same to save the amount of RAM.

Abstract: In this thesis we study aspects of Hamiltonian models which can affect the time evolution of transmon systems. We model the time evolution of various systems as a unitary real-time process by numerically solving the time-dependent Schr\"odinger equation (TDSE). We denote the corresponding computer models as non-ideal gate-based quantum computer (NIGQC) models since transmons are usually used as transmon qubits in superconducting prototype gate-based quantum computers (PGQCs).We first review the ideal gate-based quantum computer (IGQC) model and provide a distinction between the IGQC, PGQCs and the NIGQC models we consider in this thesis. Then, we derive the circuit Hamiltonians which generate the dynamics of fixed-frequency and flux-tunable transmons. Furthermore, we also provide clear and concise derivations of effective Hamiltonians for both types of transmons. We use the circuit and effective Hamiltonians we derived to define two many-particle Hamiltonians, namely a circuit and an associated effective Hamiltonian. The interactions between the different subsystems are modelled as dipole-dipole interactions. Next, we develop two product-formula algorithms which solve the TDSE for the Hamiltonians we defined. Afterwards, we use these algorithms to investigate how various frequently applied assumptions affect the time evolution of transmon systems modelled with the many-particle effective Hamiltonian when a control pulse is applied. Here we also compare the time evolutions generated by the effective and circuit Hamiltonian. We find that the assumptions we investigate can substantially affect the time evolution of the probability amplitudes we model. Next, we investigate how susceptible gate-error quantifiers are to assumptions which make up the NIGQC model. We find that the assumptions we consider clearly affect gate-error quantifiers like the diamond distance and the average infidelity.

Abstract: We study the emission spectrum of two distant qubits strongly coupled to a waveguide by using the numerical and analytical approaches, which are beyond the Markovian approximation and the rotating-wave approximation (RWA). The numerical approach combines the Dirac-Frenkel time-dependent variational principle with the multiple Davydov $D_{1}$ ansatz. A transformed RWA (TRWA) treatment and a standard perturbation (SP) are used to analytically calculate the emission spectrum. It is found that the variational approach and the TRWA treatment yield accurate emission spectra of the two distant qubits in certain strong coupling regimes while the SP breaks down. The emission spectrum is found to be asymmetric irrespective of the two-qubit distance and exhibits a single peak, doublet, and multipeaks depending on the two-qubit distance as well as the initial states. In sharply contrast with the single-qubit case, the excited-state populations of the two qubits can ultraslowly decay due to the subradiance even in the presence of a strong qubit-waveguide coupling, which in turn yields ultranarrow emission line. Our results provide insights into the emission spectral features of the two distant qubits in the strong light-matter coupling regime.

Abstract: Quantum computers hold the promise of executing tasks beyond the capability of classical computers. Noise competes with coherent evolution and destroys long-range correlations, making it an outstanding challenge to fully leverage the computation power of near-term quantum processors. We report Random Circuit Sampling (RCS) experiments where we identify distinct phases driven by the interplay between quantum dynamics and noise. Using cross-entropy benchmarking, we observe phase boundaries which can define the computational complexity of noisy quantum evolution. We conclude by presenting an RCS experiment with 70 qubits at 24 cycles. We estimate the computational cost against improved classical methods and demonstrate that our experiment is beyond the capabilities of existing classical supercomputers.

Abstract: The quantum dynamics of spin systems with uniform all-to-all interaction are often studied in the totally symmetric space (TSS) of maximal total spin. However the TSS states are atypical in the full many-body Hilbert space. In this work, we explore several aspects of the all-to-all quantum dynamics away from the TSS, and reveal surprising features of the "deep Hilbert space" (DHS). We study the out-of-time order correlator (OTOC) in the infinite-temperature ensemble of the full Hilbert space. We derive a phase-space representation of the DHS OTOC and show that the OTOC can grow super-exponentially in the large $N$ limit, due to the fast dynamics in an unbounded phase space. By a similar mechanism, the Krylov complexity grows explosively. We also study the entanglement growth in a quantum quench from a DHS product state, i.e., one of non-aligned spins that resemble the DHS infinite-temperature ensemble with respect to the statistics of the collective spins. Using a field-theoretical method, We exactly calculate the entanglement entropy in the large $N$ limit. We show that, in the DHS, fast OTOC growth does not imply fast entanglement growth, in contrast to the Zurek-Paz relation derived in the TSS.

Abstract: Contemporary quantum computers encode and process quantum information in binary qubits (d = 2). However, many architectures include higher energy levels that are left as unused computational resources. We demonstrate a superconducting ququart (d = 4) processor and combine quantum optimal control with efficient gate decompositions to implement high-fidelity ququart gates. We distinguish between viewing the ququart as a generalized four-level qubit and an encoded pair of qubits, and characterize the resulting gates in each case. In randomized benchmarking experiments we observe gate fidelities greater 95% and identify coherence as the primary limiting factor. Our results validate ququarts as a viable tool for quantum information processing.