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## Introduction quantumcat is a platform-independent, open-source, high-level quantum computing library, which allows the quantum community to focus on developing platform-independent quantum applications without much effort. ## It is based on two principles: 1) Write once and execute on any supported quantum provider using one syntax 2) quantumcat should enable researchers and developers to create quantum applications using high-level programming in the future so that they can focus on developing quantum applications instead of learning low-level concepts such as gates and circuits ### Write once ```python from quantumcat.utils import providers num_of_qubits = 2 qc = QCircuit(num_of_qubits) qc.h_gate(0) qc.cx_gate(0, 1) # To execute on Google Cirq result = qc.execute(provider=providers.GOOGLE_PROVIDER, repetitions=1024) ``` ```python # To execute on IBM Qiskit result = qc.execute(provider=providers.IBM_PROVIDER, repetitions=1024) ``` ```python # To execute on Amazon Braket result = qc.execute(provider=providers.AMAZON_PROVIDER, repetitions=1024) ``` ### Compare the results of all the supported providers with a single line of code ```python # Execute on All providers in one go circuit.compare_results(plot=True) ```

### Execute on real IBM quantum hardware with quantumcat ```python from quantumcat.utils import providers result = qc.execute(provider=providers.IBM_PROVIDER, api='API KEY from IBM Quantum dashboard', device='IBM DEVICE NAME such as ibmq_manila or ibmq_quito') # Copy API and Device name from https://quantum-computing.ibm.com/ ``` ## Installation ```shell pip install quantumcat ``` ## Platforms Supported * Google Cirq * IBM Qiskit * Amazon Braket * IonQ (Via Braket) * Rigetti (Via Braket) ## Examples of High-Level Functions ### Deutsch Jozsa Algorithm ```python deutsch_jozsa = DeutschJozsa('balanced', 4) print(deutsch_jozsa.execute(provider=providers.IBM_PROVIDER)) ``` ### Superposition ```python qc.superposition(0) # puts qubit 0 in superposition ``` ### Entanglement ```python qc.entangle(0, 1) # entangles qubit 0 with qubit 1 ``` ### Phase Kickback ```python qc.phase_kickback(0) # applies |-> to qubit 0 ``` ## Example of High-Level Applications ### Random Number Generator ```python from quantumcat.utils import providers, constants from quantumcat.applications.generator import RandomNumber random_number = RandomNumber(length=2, output_type=constants.DECIMAL).execute(provider=providers.GOOGLE_PROVIDER) print(random_number) # To generate random number on actual IBM device random_number = RandomNumber(length=2, output_type=constants.DECIMAL) .execute(provider=providers.IBM_PROVIDER, repetitions=1024, api='API KEY from IBM Quantum dashboard' device='IBM DEVICE NAME such as ibmq_manila or ibmq_quito') print(random_number) ``` ### Password Generator ```python from quantumcat.applications.generator import Password password = Password(8).generate() print(password) # Length should be between 5 - 20 # Password is generated in hexadecimal format using QRNG@ANU JSON API ``` ### OTP Generator ```python from quantumcat.applications.generator import OTP otp = OTP().generate() print(otp) # 5 digits OTP is generated using QRNG@ANU JSON API ``` ## Examples of Low-Level Functions ### Circuit Creation ```python from quantumcat.circuit import QCircuit num_of_qubits = 3 qc = QCircuit(num_of_qubits) ``` ### Single-Qubit Gate ```python qc.x_gate(0) # applies X gate on qubit 0 ``` ### Two-Qubit Gate ```python qc.cx_gate(0, 1) # control qubit, target qubit ``` ### Multi-Qubit Gate ```python qc.mct_gate([0, 1], 2) # control qubits array, target qubit ``` ### Draw Circuit ```python from quantumcat.utils import providers qc.draw_circuit(provider=providers.GOOGLE_PROVIDER) ``` ## Gates Supported [Click here to view gates supported](https://drive.google.com/file/d/1XNCY2NyioTpqNII4dalm4plKE2-suKYB/view) ## Visualization ### Histogram ```python circuit = QCircuit(1) circuit.superposition(0) counts = circuit.execute(provider=providers.GOOGLE_PROVIDER, repetitions=1024) circuit.histogram(counts) ```

### Bloch Multivector ```python circuit = QCircuit(1) circuit.superposition(0) state = circuit.execute(provider=providers.GOOGLE_PROVIDER, simulator_name=constants.STATEVECTOR_SIMULATOR) circuit.bloch_multivector(state) ```

### QSphere ```python circuit = QCircuit(1) circuit.superposition(0) state = circuit.execute(provider=providers.GOOGLE_PROVIDER, simulator_name=constants.STATEVECTOR_SIMULATOR) circuit.state_qsphere(state) ```

## License [Apache License 2.0](LICENSE.txt) 16:["$","$L1f",null,{"user":{"username":"artificial-brain","displayName":"Artificial Brain","bio":null,"location":null,"githubUrl":"https://github.com/artificial-brain","avatar":null,"memberSince":null,"stats":{"algorithms":1,"totalStars":27,"totalForks":18,"contributions":1}},"userRepos":[{"id":"artificial-brain-quantumcat","slug":"artificial-brain-quantumcat","type":"framework","name":"quantumcat","description":"quantumcat is a platform-independent, open-source, high-level quantum computing library, which allows the quantum community to focus on developing platform-independent quantum applications without much effort.","summary":"$undefined","useCases":[],"fullName":"artificial-brain/quantumcat","githubUrl":"https://github.com/artificial-brain/quantumcat","author":"artificial-brain","authorType":"organization","metadata":{"framework":null,"frameworks":[],"taskType":null,"tags":["cross-platform","high-level-programming","quantum-algorithms","quantum-applications","quantum-computing","quantum-library"],"hardwareCompatibility":[],"qubitRequirement":null,"license":"Apache-2.0","installCommand":"$undefined","maturity":"$undefined"},"stats":{"stars":27,"forks":18,"downloads":0,"runs":0,"lastUpdated":"2024-01-03T04:46:38Z","createdAt":"2021-03-31T12:11:05Z"},"features":{"verified":false,"trending":false,"featured":false},"version":"1.0.0","readme":"$20","benchmarks":[],"papers":[]}]}]

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