<jupyter_start><jupyter_text>How To Find Out Whether To Pursue A Career In Quantum Computing — Today!This post appeared first on [Medium](https://pyqml.medium.com/how-to-find-out-whether-to-pursue-a-career-in-quantum-computing-today-d1c7093811e8) and my weekly [email-course](https://pyqml.substack.com/p/how-to-find-out-whether-to-pursue?s=w).Quantum computing is one of the most hyped topics today! But, let’s face it — it is not precisely a beginner-friendly field. You need to be highly proficient in math, physics, and computer science.![](./assets/phd.png)This is a severe problem for anyone interested in pursuing a career in this field because you’ll probably need to have already completed your university studies before you can get your hands on actual problems in the field.That’s not exactly the least risky way to find out whether or not a career in quantum computing is right for you.So, what do you do instead? — How about working on a specific problem in the field that someone is willing to spend $100,000\$$ on?Here’s the deal. IBM just announced its second Quantum Open Science Prize. They ask for a solution to a quantum simulation problem. They want us to simulate a Heisenberg model Hamiltonian for a three-particle system on IBM Quantum’s 7-qubit Jakarta system using Trotterization.Don’t worry — yet. Of course, IBM explains what a Heisenberg model Hamiltonian and Trotterization are in the material appended to the announcement.The Heisenberg Hamiltonian $H_{Heis}$ is defined as$\begin{equation}H_{\text{Heis}} = \sum_{\langle ij \rangle}^{N} J \left(\sigma_x^{(i)}\sigma_x^{(j)} + \sigma_y^{(i)}\sigma_y^{(j)} + \sigma_z^{(i)}\sigma_z^{(j)}\right).\end{equation}$ with 𝑁 is the number of spin-1/2 particles in the model, 𝜎𝑥, 𝜎𝑦, and 𝜎𝑧 are Pauli operators, and the 𝑖 and 𝑗 superscripts label which qubit they act on.Trotterization refers to a method of simulating the sum-of-terms of a Hamiltonian by simulating each one separately for a small-time slice.Everything’s clear. — Of course, it’s not! Do worry — now.I appreciate all the effort the IBM folks invested in the material preparation. But it clearly addresses a single audience: quantum physicists!So, we’re back where we started. You’d have to earn your physics degree before you could get your hands dirty on the task.Don’t give up that fast. You can learn a lot from this announcement alone on whether a career in quantum computing is right for you or not.First, let’s talk about all this physics jargon. You better get used to it. I mean, you don’t need to understand all of it right away. But, if you end up in a quantum computing career eventually, you’ll need to work yourself through these equations. It’s comparable to being a software developer and reading someone else’s code. It’s part of the job.Second, let’s look at the code. IBM provides a working example of the code they expect from us. It’s a lot longer than the following snippet, but this gives you the first impression of it.<jupyter_code>### YOUR TROTTERIZATION GOES HERE -- START (beginning of example)

# Parameterize variable t to be evaluated at t=pi later
t = Parameter('t')
# Build a subcircuit for XX(t) two-qubit gate
XX_qr = QuantumRegister(2)
XX_qc = QuantumCircuit(XX_qr, name='XX')

XX_qc.ry(np.pi/2,[0,1])

...

# Convert custom quantum circuit into a gate
ZZ = ZZ_qc.to_instruction()
Combine subcircuits into single gate representing one ($n=1$) trotter step.

# Combine subcircuits into a single multiqubit gate representing a single trotter step
num_qubits = 3

Trot_qr = QuantumRegister(num_qubits)
Trot_qc = QuantumCircuit(Trot_qr, name='Trot')

for i in range(0, num_qubits - 1):
    Trot_qc.append(ZZ, [Trot_qr[i], Trot_qr[i+1]])
    Trot_qc.append(YY, [Trot_qr[i], Trot_qr[i+1]])
    Trot_qc.append(XX, [Trot_qr[i], Trot_qr[i+1]])

# Convert custom quantum circuit into a gate
Trot_gate = Trot_qc.to_instruction()

### YOUR TROTTERIZATION GOES HERE -- FINISH (end of example)<jupyter_output><empty_output>
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