Patents by Inventor Matthew Hastings

Matthew Hastings has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11669763
    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.
    Type: Grant
    Filed: April 23, 2019
    Date of Patent: June 6, 2023
    Assignee: Microsoft Technology Licensing, LLC
    Inventor: Matthew Hastings
  • Publication number: 20230115086
    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.
    Type: Application
    Filed: May 11, 2022
    Publication date: April 13, 2023
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Matthew HASTINGS, Jeongwan HAAH
  • Publication number: 20230027698
    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.
    Type: Application
    Filed: June 30, 2021
    Publication date: January 26, 2023
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Matthew Hastings, Jeongwan Haah
  • Patent number: 11038537
    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.
    Type: Grant
    Filed: August 30, 2019
    Date of Patent: June 15, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Jeongwan Haah, David Wecker, Matthew Hastings, David Poulin
  • Patent number: 10846608
    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.
    Type: Grant
    Filed: May 17, 2018
    Date of Patent: November 24, 2020
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Jeongwan Haah, Matthew Hastings
  • Publication number: 20200202249
    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.
    Type: Application
    Filed: April 23, 2019
    Publication date: June 25, 2020
    Applicant: Microsoft Technology Licensing, LLC
    Inventor: Matthew Hastings
  • Patent number: 10574268
    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.
    Type: Grant
    Filed: June 14, 2017
    Date of Patent: February 25, 2020
    Assignee: Microsoft Technology Licensing, LLC
    Inventor: Matthew Hastings
  • Publication number: 20190386685
    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.
    Type: Application
    Filed: August 30, 2019
    Publication date: December 19, 2019
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Jeongwan Haah, David Wecker, Matthew Hastings, David Poulin
  • Patent number: 10417370
    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.
    Type: Grant
    Filed: February 6, 2015
    Date of Patent: September 17, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Matthew Hastings, David Wecker
  • Patent number: 10404287
    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.
    Type: Grant
    Filed: June 19, 2017
    Date of Patent: September 3, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Jeongwan Haah, David Wecker, Matthew Hastings, David Poulin
  • Publication number: 20190266213
    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.
    Type: Application
    Filed: February 26, 2019
    Publication date: August 29, 2019
    Applicant: Microsoft Technology Licensing, LLC
    Inventor: Matthew Hastings
  • Patent number: 10346348
    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.
    Type: Grant
    Filed: June 28, 2017
    Date of Patent: July 9, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Matthew Hastings, Torsten Karzig, Parsa Bonderson, Michael Freedman, Roman Lutchyn, Chetan Nayak
  • Publication number: 20190087474
    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.
    Type: Application
    Filed: September 12, 2018
    Publication date: March 21, 2019
    Inventors: Stefan Anastas Nagey, James Charles Bursa, Samuel Vincent Scarpino, Conor Matthew Hastings, Agastya Mondal, Michael Roytman
  • Publication number: 20190087475
    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.
    Type: Application
    Filed: September 12, 2018
    Publication date: March 21, 2019
    Inventors: Stefan Anastas Nagey, James Charles Bursa, Samuel Vincent Scarpino, Conor Matthew Hastings, Agastya Mondal, Michael Roytman
  • Publication number: 20190080254
    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.
    Type: Application
    Filed: May 17, 2018
    Publication date: March 14, 2019
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Jeongwan Haah, Matthew Hastings
  • Patent number: 10176433
    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.
    Type: Grant
    Filed: March 13, 2017
    Date of Patent: January 8, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Matthew Hastings, David Wecker
  • Publication number: 20180269906
    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.
    Type: Application
    Filed: June 19, 2017
    Publication date: September 20, 2018
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Jeongwan Haah, David Wecker, Matthew Hastings, David Poulin
  • Publication number: 20180248566
    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.
    Type: Application
    Filed: June 14, 2017
    Publication date: August 30, 2018
    Applicant: Microsoft Technology Licensing, LLC
    Inventor: Matthew Hastings
  • Publication number: 20180052806
    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.
    Type: Application
    Filed: June 28, 2017
    Publication date: February 22, 2018
    Applicant: Microsof Technology Licensing, LLC
    Inventors: Matthew Hastings, Torsten Karzig, Parsa Bonderson, Michael Freedman, Roman Lutchyn, Chetan Nayak
  • Publication number: 20170330101
    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.
    Type: Application
    Filed: March 13, 2017
    Publication date: November 16, 2017
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Matthew Hastings, David Wecker