Coverage for jaxquantum/devices/superconducting/truncated_transmon.py: 0%

1"""Transmon.""" 

2 

3from flax import struct 

4from jax import config 

5 

6import jax.numpy as jnp 

7import jax.scipy as jsp 

8 

9from jaxquantum.devices.superconducting.flux_base import FluxDevice 

10from jaxquantum.core.operators import identity, destroy, create 

11 

12config.update("jax_enable_x64", True) 

13 

14 

15@struct.dataclass 

16class TruncatedTransmon(FluxDevice): 

17 """ 

18 Transmon Device. 

19 """ 

20 

21 def common_ops(self): 

22 """Written in the linear basis.""" 

23 

24 ops = {} 

25 

26 N = self.N_pre_diag 

27 ops["id"] = identity(N) 

28 ops["a"] = destroy(N) 

29 ops["a_dag"] = create(N) 

30 ops["phi"] = self.phi_zpf() * (ops["a"] + ops["a_dag"]) 

31 ops["n"] = 1j * self.n_zpf() * (ops["a_dag"] - ops["a"]) 

32 return ops 

33 

34 def phi_zpf(self): 

35 """Return Phase ZPF.""" 

36 return (2 * self.params["Ec"] / self.params["Ej"]) ** (0.25) 

37 

38 def n_zpf(self): 

39 """Return Charge ZPF.""" 

40 return (self.params["Ej"] / (32 * self.params["Ec"])) ** (0.25) 

41 

42 def get_linear_ω(self): 

43 """Get frequency of linear terms.""" 

44 return jnp.sqrt(8 * self.params["Ec"] * self.params["Ej"]) 

45 

46 def get_H_linear(self): 

47 """Return linear terms in H.""" 

48 w = self.get_linear_ω() 

49 return w * self.linear_ops["a_dag"] @ self.linear_ops["a"] 

50 

51 def get_H_full(self): 

52 """Return full H in linear basis.""" 

53 cos_phi_op = ( 

54 jsp.linalg.expm(1j * self.linear_ops["phi"]) 

55 + jsp.linalg.expm(-1j * self.linear_ops["phi"]) 

56 ) / 2 

57 

58 H_nl = -self.params["Ej"] * cos_phi_op - self.params[ 

59 "Ej" 

60 ] / 2 * jnp.linalg.matrix_power(self.linear_ops["phi"], 2) 

61 return self.get_H_linear() + H_nl 

62 

63 def potential(self, phi): 

64 """Return potential energy for a given phi.""" 

65 return -self.params["Ej"] * jnp.cos(2 * jnp.pi * phi)