CDI Training

Optical Hardware Optomechanics, apart from being a very clever-sounding word, is the technical term for all the bits of hardware used to mount and manipulate optics. This section will walk you through some of the basic hardware you’ll use when working with optics. All images in this section come from Thorlabs, since that's mostly the equipment we have in the lab. First, here are a few of the more common pieces of hardware.

This article is meant as a crash course lesson in the important mathematical foundations behind our research such as Taylor Series, Sine Waves and Complex Exponentials. Explore the links and practice each concept to deepen your understanding and expand your foundation.

a. “Pink” beam (i.e. x-raynbow, lots of wavelengths)

Signal vs. Noise Perhaps the most important skill in signal processing[1] is the ability to separate important data (signal) from irrelevant data (noise). The human brain is naturally pretty good at this, which is whi you can sitll camprehend tihs sntence. Computers, on the other hand, are naturally very bad at it, which is why a single missing semicolon can crash an entire server. This has become a major problem, since modern science depends so heavily on computers, and has brought about some really creative techniques[2] to handle noisy data. Even with these clever algorithms, however, less noise is always better than more noise.

The fact that detectors can only capture part of the information in a diffraction pattern is called the phase problem. Phase retrieval is exactly what it sounds like: retrieving the information that was in the phase of the diffraction pattern. Before we look at how this is done, however, I want to drive home how ridiculous of a problem this is.

Diffraction Diffraction is a phenomenon that occurs when a wavefront changes shape after being partially blocked, either by an object or an aperture.

The underpinning concept behind coherent diffractive imaging (CDI) is that diffraction is predictable. Brilliant physicists with names that begin with F, such as Fraunhofer, Fresnel, and Fourier have given us incredibly detailed equations to describe how light behaves after interacting with objects.[1] Specifically, we know that far-field diffraction patterns are Fourier transforms of the objects that cause them. If you know the object, you can calculate diffraction pattern, and vice versa.

Here's some examples of CDI code that might be useful.

There’s a good chance that most (if not all) of the math you’ve learned so far has been analytical, meaning that solutions are found by manipulating symbols according to the many rules of algebra, calculus, geometry, etc. However, this is not the only way to do math. In numerical mathematics, every symbol is given an approximate value, and then the values are manipulated to give an approximate solution. Where analytical analysis typically involves doing a small number of difficult steps to arrive at an exact solution; numerical analysis typically involves doing a huge number of very easy steps to arrive at a good approximate solution. And, believe it or not, sometimes an approximation is more useful than an exact solution.1

Presenting research can be daunting, but it is very fun! It is an opportunity for one to show what they are trying to contribute to the world and why it is worth pursuing. The following are some tips and tricks that can make presenting less intimidating and more exciting. Before diving in remember these are general tips meant to help one shape their presentation. This is NOT a strict list of things that a presentation should be.

Acronyms are used a lot in scientific research due to the exceptionally long names that are created to be more descriptive. Unfortunately, once we start to use acronyms, the names are no longer descriptive at all. Familiarizing yourself with these acronyms will help you keep up in technical conversations, but don't be afraid to ask someone what an acronym means. In presentations and papers, you should always use the full name first and link that to the acronym, before referring to anything solely by its acronym.

Safety is very important in the lab setting, both for those working in the lab and the equipment in the lab.

Programming languages When people with no common language need to communicate, they develop something called a pidgin—a sort of simplified combination of their native languages. At its core, a programming language is a pidgin: a way for people (who don’t speak machine code) to communicate with computers (which only speak machine code). I’ve found that this approach to programming really helps when things get frustrating. It can be very difficult to communicate complex ideas in a language with no native speakers.

Academic literature is not like other literature. It is not exciting. It is not amusing.[1] It is not suspenseful. If I had to pick one word to describe it, it would be “viscous.” It’s like literary molasses: hard to get through, easy to get stuck in. The following strategies can help you get through even the densest papers. These ideas are taken from my own experience, as well as from an excellent compilation of tips and tricks from scientists around the world, published in Science magazine.

“You’ve taken your first steps into a larger world.”