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Physically Defined Coupled Silicon Quantum Dots Containing a Few Electrons for Electron Spin Qubits
Published in Simon Deleonibus, Emerging Devices for Low-Power and High-Performance Nanosystems, 2018
Tetsuo Kodera, Kosuke Horibe, Shunri Oda
Recently, significant progress has been made in electron spin qubits in silicon. A singlet-triplet qubit in a DQD based on Si/SiGe heterostructures has been demonstrated [5]. In the singlet-triplet qubit, manipulations of spins by exchange interactions have been demonstrated with a spin dephasing time T2* of 360 ns. In another study, a longitudinal spin relaxation time T1 of 10 ms at zero magnetic field is extended to T1 = 3 s for triplet states at B = 1 T in singlet-triplet qubits [28]. A singlet-triplet qubit has also been studied in a DQD based on the coupled phosphorus dimers in Si, and T1 was measured to be 4 ms [29]. Single-electron spin qubits in QDs based on Si/SiGe heterostructures [30, 31], Si MOS structures [32, 33], and phosphorus donors in Si [34] have been reported. In Ref. [32], manipulation of single-electron spin qubits has been achieved by using ESR, with a long dephasing time T2* of 63 ns. Furthermore, a controlled-NOT gate of 2-qubit operation has been realized in a DQD based on isotopically enriched Si MOS structures [7].
Function Optimization Using IBM Q
Published in Siddhartha Bhattacharyya, Mario Köppen, Elizabeth Behrman, Ivan Cruz-Aceves, Hybrid Quantum Metaheuristics, 2022
Siddhartha Bhattacharyya, Mario Köppen, Elizabeth Behrman, Ivan Cruz-Aceves
A sample QISKit code has been written to create a quantum circuit using a Hadamard gate H on qubit 0, a Controlled-X gate on control qubit 0 and target qubit 1 and measure on each qubit to visualize the result. In Figure 3.9, a sample circuit has been drawn using QISKit programming and Figure 3.10 shows simulation and plotting the result.
Quantum computing methods for electronic states of the water molecule
Published in Molecular Physics, 2019
Teng Bian, Daniel Murphy, Rongxin Xia, Ammar Daskin, Sabre Kais
Some work has been done on this track to solve the resonance problem by quantum computers. By designing a general quantum circuit for non-unitary matrices, Daskin et al. [36] explored the resonance states of a model non-Hermitian Hamiltonian. To be specific, he introduced a systematic way to estimate the complex eigenvalues of a general matrix using the standard iterative phase estimation algorithm with a programmable circuit design. The bit values of the phase qubit determines the phase of eigenvalue, and the statistics of outcomes of the measurements on the phase qubit determines the absolute value of the eigenvalue. Other approaches for solving complex eigenvalues can also be applied for this resonance problem. For example, Wang et al. [37] proposed a measurement-based quantum algorithms for finding eigenvalues of non-unitary matrices. Terashima and Ueda [38] introduced a universal non-unitary quantum circuit by using a specific type of one-qubit non-unitary gates, the controlled-NOT gate, and all one-qubit unitary gates, which is also useful for finding the eigenvalues of a non-hermitian Hamiltonian matrix.
Multiple-Controlled Toffoli and Multiple-Controlled Fredkin Reversible Logic Gates-Based Reversible Synchronous Counter Design
Published in IETE Journal of Research, 2023
S. K. Binu Siva Singh, K. V. Karthikeyan
Quantum gates are the building blocks of quantum circuits, and they manipulate the state of qubits. In classical computing, logic gates such as AND, OR, and NOT gates are used to manipulate the state of bits. In quantum computing, there are a few universal gates that can be utilized to construct quantum circuits. One of these is the Toffoli gate, a three-qubit gate that functions similarly to a conventional AND gate. Another three-qubit gate is the Fredkin gate, also known as the controlled-SWAP gate, which swaps the second and third qubits if the first qubit is in the state.
An entangling-probe attack on Shor’s algorithm for factorization
Published in Journal of Modern Optics, 2018
Utilization of entanglement to steal information of the quantum cryptographic protocol in key distribution has been investigated in several strategies [1–5]. In these attacks, first, Eve (an eavesdropper) lets a carrier qubit of Alic and Bob (a sender and a receiver) interact with her own qubit, called as a probe, so that the carrier qubit and the probe are in an entangled state. Next, Eve measures her own probe and obtains information about the key distribution. In Reference [1], the general eavesdropping attack with the probe and its trade-off between the information gain and disturbance are investigated. In Reference [2], individual attacks with the probe against the four-state Bennett–Brassard 1984 (BB84) and the two-state Bennett 1992 (B92) quantum cryptographic protocols are examined [6,7]. In Reference [3], for the interaction of the entangling probe with signal basis states of the BB84 protocol, some optimized unitary transformations are calculated. In Reference [4], it is discussed how to realize the Fuchs–Peres–Brandt (FPB) entangling probe physically using a deterministic controlled-NOT gate implemented with single-photon two-qubit (SPTQ) quantum logic. In Reference [5], physical simulation of the FPB probe with the SPTQ logic is discussed, including physical errors. Moreover, as an advanced version, Eve can let her probe interact with more than one of Alice and Bob’s qubits simultaneously, which is called as a coherent attack [8]. In Reference [9], Eve’s optimal information gained in coherent attacks is estimated for the six-state protocol, which is another version of the BB84 protocol and discussed in Reference [10]. It is considered that coherent measurements can supply much more information than incoherent individual measurements can do [11]. Because Eve can steal information from quantum cryptographic protocols with entangling probes as mentioned above, we may expect to do exactly same for attacking quantum algorithms. This is the primary motivation of the current paper.