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Getting Real: The Smarter, Faster, Easier Way to Build a Web Application

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37Signals

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“Similarly, the computers used to run the software on the ground for the mission were borrowed from a previous mission. These machines were so out of date that Bowman had to shop on eBay to find replacement parts to get the machines working. As systems have gone obsolete, JPL no longer uses the software, but Bowman told me that the people on her team continue to use software built by JPL in the 1990s, because they are familiar with it. She said, “Instead of upgrading to the next thing we decided that it was working just fine for us and we would stay on the platform.” They have developed so much over such a long period of time with the old software that they don’t want to switch to a newer system. They must adapt to using these outdated systems for the latest scientific work. Working within these constraints may seem limiting. However, building tools with specific constraints—from outdated technologies and low bitrate radio antennas—can enlighten us. For example, as scientists started to explore what they could learn from the wait times while communicating with deep space probes, they discovered that the time lag was extraordinarily useful information. Wait times, they realized, constitute an essential component for locating a probe in space, calculating its trajectory, and accurately locating a target like Pluto in space. There is no GPS for spacecraft (they aren’t on the globe, after all), so scientists had to find a way to locate the spacecraft in the vast expanse. Before 1960, the location of planets and objects in deep space was established through astronomical observation, placing an object like Pluto against a background of stars to determine its position.15 In 1961, an experiment at the Goldstone Deep Space Communications Complex in California used radar to more accurately define an “astronomical unit” and help measure distances in space much more accurately.16 NASA used this new data as part of creating the trajectories for missions in the following years. Using the data from radio signals across a wide range of missions over the decades, the Deep Space Network maintained an ongoing database that helped further refine the definition of an astronomical unit—a kind of longitudinal study of space distances that now allows missions like New Horizons to create accurate flight trajectories. The Deep Space Network continued to find inventive ways of using the time lag of radio waves to locate objects in space, ultimately finding that certain ways of waiting for a downlink signal from the spacecraft were less accurate than others. It turned to using the antennas from multiple locations, such as Goldstone in California and the antennas in Canberra, Australia, or Madrid, Spain, to time how long the signal took to hit these different locations on Earth. The time it takes to receive these signals from the spacecraft works as a way to locate the probes as they are journeying to their destination. Latency—or the different time lag of receiving radio signals on different locations of Earth—is the key way that deep space objects are located as they journey through space. This discovery was made possible during the wait times for communicating with these craft alongside the decades of data gathered from each space mission. Without the constraint of waiting, the notion of using time as a locating feature wouldn’t have been possible.”

SoftwareConstraintsHardwareJplOut Of DateSpace Signals
Book:Delayed Response: The Art of Waiting from the Ancient to the Instant World
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