Abstract: A quantum error correcting code with dynamically generated logical qubits is provided. When viewed as a subsystem code, the code has no logical qubits. Nevertheless, the measurement patterns generate logical qubits, allowing the code to act as a fault-tolerant quantum memory. Each measurement can be a two-qubit Pauli measurement.

Abstract: A quantum error correcting code with dynamically generated logical qubits is provided. When viewed as a subsystem code, the code has no logical qubits. Nevertheless, the measurement patterns generate logical qubits, allowing the code to act as a fault-tolerant quantum memory. Each measurement can be a two-qubit Pauli measurement.

Abstract: Disclosed herein are example embodiments of protocols to distill magic states for T-gates. Particular examples have low space overhead and use an asymptotically optimal number of input magic states to achieve a given target error. The space overhead, defined as the ratio between the physical qubits to the number of output magic states, is asymptotically constant, while both the number of input magic states used per output state and the T-gate depth of the circuit scale linearly in the logarithm of the target error. Unlike other distillation protocols, examples of the disclosed protocol achieve this performance without concatenation and the input magic states are injected at various steps in the circuit rather than all at the start of the circuit. Embodiments of the protocol can be modified to distill magic states for other gates at the third level of the Clifford hierarchy, with the same asymptotic performance.

Abstract: This application concerns quantum computing and quantum circuits. For example, among the embodiments disclosed herein are codes and protocols to distill T, controlled-S, and Toffoli (or CCZ) gates for use in croantum circuits. Examples of the disclosed codes use lower overhead for a given target accuracy relative to other distillation techniques. In some embodiments, a magic state distillation protocol is generated for creating magic states in the quantum computing device, wherein the magic state distillation protocol includes (a) Reed-Muller codes, or (b) punctured Reed-Muller codes. The quantum computing device can then configured to implement the magic state distillation protocol.

Abstract: In this disclosure, example quantum algorithms for approximate optimization based on a sudden quench of a Hamiltonian. While the algorithm is general, it is analyzed in this disclosure in the specific context of MAX-EK-LIN2, for both even and odd K. It is to be understood, however, that the algorithm can be generalized to other contexts. A duality can be found: roughly, either the algorithm provides some nontrivial improvement over random or there exist many solutions which are significantly worse than random. A classical approximation algorithm is then analyzed and a similar duality is found, though the quantum algorithm provides additional guarantees in certain cases.

Abstract: The disclosed technology concerns tools and techniques for implementing error-correction codes in a quantum computing device. In particular embodiments, Majorana fermion stabilizer codes having small numbers of modes and distance are disclosed. Particular embodiments have an upper bound on the number of logical qubits for distance 4 codes, and Majorana fermion codes are constructed that saturate this bound. Other distance 4 and 6 codes are also disclosed.

Abstract: Disclosed herein are example embodiments of protocols to distill magic states for T-gates. Particular examples have low space overhead and use an asymptotically optimal number of input magic states to achieve a given target error. The space overhead, defined as the ratio between the physical qubits to the number of output magic states, is asymptotically constant, while both the number of input magic states used per output state and the T-gate depth of the circuit scale linearly in the logarithm of the target error. Unlike other distillation protocols, examples of the disclosed protocol achieve this performance without concatenation and the input magic states are injected at various steps in the circuit rather than all at the start of the circuit. Embodiments of the protocol can be modified to distill magic states for other gates at the third level of the Clifford hierarchy, with the same asymptotic performance.

Abstract: Quantum computations based on second quantization are performed by applying one body and two body terms in a selected order. Typically, terms associated with operators that commute are applied prior to application of other terms. In a particular example, one body terms of the form hpp are applied first, followed by two body terms of the form hprrp.

Abstract: Disclosed herein are example embodiments of protocols to distill magic states for T-gates. Particular examples have low space overhead and use an asymptotically optimal number of input magic states to achieve a given target error. The space overhead, defined as the ratio between the physical qubits to the number of output magic states, is asymptotically constant, while both the number of input magic states used per output state and the T-gate depth of the circuit scale linearly in the logarithm of the target error. Unlike other distillation protocols, examples of the disclosed protocol achieve this performance without concatenation and the input magic states are injected at various steps in the circuit rather than all at the start of the circuit. Embodiments of the protocol can be modified to distill magic states for other gates at the third level of the Clifford hierarchy, with the same asymptotic performance.

Abstract: Disclosed herein are example quantum algorithms to solve certain problems (e.g., exactly) in combinatorial optimization, including weighted MAX-2-SAT as well as problems where the objective function is a weighted sum of products of Ising variables, all terms of the same degree D; this problem is called weighted MAX-ED-LIN2. In some cases, it is desirable that the optimal solution be unique for odd D and doubly degenerate for even D; however, example algorithms still work without this condition and it is shown how to reduce to the case without this assumption at the cost of an additional overhead.

Abstract: Among the embodiments disclosed herein are example methods for generating all Clifford gates for a system of Majorana Tetron qubits (quasiparticle poisoning protected) given the ability to perform certain 4 Majorana zero mode measurements. Also disclosed herein are example designs for scalable quantum computing architectures that enable the methods for generating the Clifford gates, as well as other operations on the states of MZMs. These designs are configured in such a way as to allow the generation of all the Clifford gates with topological protection and non-Clifford gates (e.g. a ?/8-phase gate) without topological protection, thereby producing a computationally universal gate set. Several possible realizations of these architectures are disclosed.

Abstract: Presented here is a system for automatic conversion of data between various data sets. In one embodiment, the system can obtain a data set, can analyze associations between the variables in the data set, and can convert the data set into a canonical data model. The canonical data model is a smaller representation of the original data set because insignificant variables and associations can be left out, and significant relationships can be represented procedurally and/or using mathematical functions. In one embodiment, part of the system can be a trained machine learning model which can convert the input data set into a canonical data model. The canonical data model can be a more efficient representation of the input data set. Consequently, various actions, such as an analysis of the data set, merging of two data sets, etc. can be performed more efficiently on the canonical data model.

Abstract: Presented here is a system for automatic conversion of data between various data sets. In one embodiment, the system can obtain a data set, can analyze associations between the variables in the data set, and can convert the data set into a canonical data model. The canonical data model is a smaller representation of the original data set because insignificant variables and associations can be left out, and significant relationships can be represented procedurally and/or using mathematical functions. In one embodiment, part of the system can be a trained machine learning model which can convert the input data set into a canonical data model. The canonical data model can be a more efficient representation of the input data set. Consequently, various actions, such as an analysis of the data set, merging of two data sets, etc. can be performed more efficiently on the canonical data model.

Abstract: This application concerns quantum computing and quantum circuits. For example, among the embodiments disclosed herein are codes and protocols to distill T, controlled-S, and Toffoli (or CCZ) gates for use in croantum circuits. Examples of the disclosed codes use lower overhead for a given target accuracy relative to other distillation techniques. In some embodiments, a magic state distillation protocol is generated for creating magic states in the quantum computing device, wherein the magic state distillation protocol includes (a) Reed-Muller codes, or (b) punctured Reed-Muller codes. The quantum computing device can then configured to implement the magic state distillation protocol.

Abstract: Among the embodiments disclosed herein are variants of the quantum approximate optimization algorithm with different parametrization. In particular embodiments, a different objective is used: rather than looking for a state which approximately solves an optimization problem, embodiments of the disclosed technology find a quantum algorithm that will produce a state with high overlap with the optimal state (given an instance, for example, of MAX-2-SAT). In certain embodiments, a machine learning approach is used in which a “training set” of problems is selected and the parameters optimized to produce large overlap for this training set. The problem was then tested on a larger problem set. When tested on the full set, the parameters that were found produced significantly larger overlap than optimized annealing times. Testing on other random instances (e.g., from 20 to 28 bits) continued to show improvement over annealing, with the improvement being most notable on the hardest problems.

Abstract: Disclosed herein are example embodiments of protocols to distill magic states for T-gates. Particular examples have low space overhead and use an asymptotically optimal number of input magic states to achieve a given target error. The space overhead, defined as the ratio between the physical qubits to the number of output magic states, is asymptotically constant, while both the number of input magic states used per output state and the T-gate depth of the circuit scale linearly in the logarithm of the target error. Unlike other distillation protocols, examples of the disclosed protocol achieve this performance without concatenation and the input magic states are injected at various steps in the circuit rather than all at the start of the circuit. Embodiments of the protocol can be modified to distill magic states for other gates at the third level of the Clifford hierarchy, with the same asymptotic performance.

Abstract: The disclosed technology concerns tools and techniques for implementing error-correction codes in a quantum computing device. In particular embodiments, Majorana fermion stabilizer codes having small numbers of modes and distance are disclosed. Particular embodiments have an upper bound on the number of logical qubits for distance 4 codes, and Majorana fermion codes are constructed that saturate this bound. Other distance 4 and 6 codes are also disclosed.

Abstract: Among the embodiments disclosed herein are example methods for generating all Clifford gates for a system of Majorana Tetron qubits (quasiparticle poisoning protected) given the ability to perform certain 4 Majorana zero mode measurements. Also disclosed herein are example designs for scalable quantum computing architectures that enable the methods for generating the Clifford gates, as well as other operations on the states of MZMs. These designs are configured in such a way as to allow the generation of all the Clifford gates with topological protection and non-Clifford gates (e.g. a ?/8-phase gate) without topological protection, thereby producing a computationally universal gate set. Several possible realizations of these architectures are disclosed.

Abstract: Among the embodiments disclosed herein are variants of the quantum approximate optimization algorithm with different parametrization. In particular embodiments, a different objective is used: rather than looking for a state which approximately solves an optimization problem, embodiments of the disclosed technology find a quantum algorithm that will produce a state with high overlap with the optimal state (given an instance, for example, of MAX-2-SAT). In certain embodiments, a machine learning approach is used in which a “training set” of problems is selected and the parameters optimized to produce large overlap for this training set. The problem was then tested on a larger problem set. When tested on the full set, the parameters that were found produced significantly larger overlap than optimized annealing times. Testing on other random instances (e.g., from 20 to 28 bits) continued to show improvement over annealing, with the improvement being most notable on the hardest problems.

Abstract: Quantum circuits for chemistry simulation are based on second quantization Hamiltonian coefficients for one-body and two-body interactions. Jordan-Wigner series that conserve parity can be defined so that selected CNOT gates are removed from the associated circuits. Basis change gates such as Hadamard or Y-gates can be coupled to some or all qubits of a quantum circuit or cancelled in view of corresponding gates in adjacent circuits. In some examples, CNOT gates can be moved to different circuit locations.